Aqueous-phase Organic Chemistry in the Atmosphere

by

Ran Zhao

A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy

Department of Chemistry University of Toronto

© Copyright by Ran Zhao 2015

ii

Aqueous-phase Organic Chemistry in the Atmosphere

Ran Zhao

Doctor of Philosophy

Department of Chemistry

University of Toronto

2015

Abstract

Atmospheric aqueous phases (i.e. cloud, fog and aerosol liquid water) are important reaction media

for the processing of organic compounds. Quantitative data on aqueous-phase organic chemistry

under the atmospheric context are sparse compared to the data from comparable gas-phase

processes. A series of studies was conducted to provide fundamental information on this topic.

An online analytical technique, Aerosol Chemical Ionization Mass Spectrometry (Aerosol CIMS),

was employed to quantitatively monitor aqueous-phase OH oxidation of glyoxal and

methylglyoxal. Quantification of all the major reaction products was achieved, permitting

complete reaction mechanisms to be presented. An unexpected class of compounds, α-

hydroxyhydroperoxide (α-HHP), was observed during the experiments, and the formation of this

class of compounds was further quantified. Formation of α-HHP can be potentially important in

aerosol liquid water, affecting aerosol toxicity and the gas-particle partitioning of small aldehydes.

Aerosol CIMS was further applied to the OH oxidation of levoglucosan, using a high mass

resolution CIMS. Unique reaction trends were observed, from which novel mechanism analysis

frameworks were introduced.

Aqueous-phase photochemical processing of a variety of light-absorbing organic compounds

(Brown Carbon (BrC)) was investigated in the laboratory. The light absorptivity of BrC was

iii

significantly altered via these processes, indicating that the chemical processing of BrC species

needs to be considered for a sound assessment of their atmospheric implications.

Finally, cloud-partitioning of a toxic compound, isocyanic acid (HNCO), was investigated in the

field, representing the first online measurement of gas-phase compounds dissolved in cloudwater.

A secondary source of HNCO in the ambient air was also observed.

Overall, aqueous-phase chemistry leads to reaction products which likely contribute to secondary

organic aerosol (SOA) formation. At the same time, aqueous-phase chemistry also facilitates the

transformation and removal of specific species with atmospheric significance (e.g. tracer

compounds, pollutants, BrC).

iv

Acknowledgments

First and foremost, I would like to thank my supervisor, Jon Abbatt, for all his contributions to this

thesis and to my entire PhD research. He has continuously impressed me with his intelligence,

generosity, fairness and considerateness. Not only has he provided adequate amount of guidance

in my research to support me, but also given me plenty of freedom so that I can learn to think

thoroughly, act critically, and work independently. His support extends to my exploration of life-

long career goals as well. He always promptly provides precious advice when I had to make

important decisions. My appreciation to Jon cannot be fully described in merely one paragraph.

Nevertheless, throughout my five years of pursuing a PhD, I realize that I could not have found a

better supervisor than him.

I would also like to give special thanks to my supervisory committee members, Jamie Donaldson

and Jen Murphy. In fact, I have worked as an undergraduate student in both of their laboratories

prior to my PhD pursuit. Without experiencing working with them, I may not have made the

decision to stay in this research area. They have also provided me with continuous support

throughout my PhD degree, with timely advice during my decision-making processes.

I also thank Frank Wania, Authur Chan, and Barbara Ervens for serving on my final examination

committee. Frank has served on my oral exam committee and provided me with useful advice

during the midpoint of my PhD degree. Arthur generously agreed on sitting in on two defences in

the same week. Barbara found a gap in her busy schedule to visit Toronto for my final defence. I

really appreciate their time and constructive suggestions on my thesis.

I have had a great opportunity working with a large number of collaborators during my PhD

research. I appreciate the support from each of them. Andre Simpson and Ron Soong at University

of Toronto Scarborough have provided me with a precious opportunity to use their advanced NMR

technique presented in Chapter 4. A number of collaborators have provided me with the biofuel

combustion samples presented in Chapter 5, including Huang Lin from Environment Canada,

Xinghua Li from Beihang University, and Fumo Yang from Chongqing institution of Green and

Intelligent Technology. A large number of collaborators have been involved in the field campaign

presented in Chapter 6. I would like to thank Richard Leaitch, Anne Marie Macdonald, John

Liggio, Jeremy Wentzell, Desiree Toom-Sauntry from Environment Canada for organizing the

campaign and allowing me to operate their Acid CIMS; Lynn Russell, Rob Modini, and Ashley

v

Corrigan from Scripps Institution of Oceanography for helping me throughout the campaign; Jason

Schroder from Allan Bertram’s group at University of British Columbia for driving me every day

to the measurement site and chasing for clouds together; and Lelia Hawkins at Harvey Mudd

College for providing me with cloudwater samples.

I was extremely fortuitous to work in a great research group. I could not have completed my PhD

degree without the support from my group members. I would like to send special thanks to Alex

Lee who is essentially my second supervisor. He has helped me throughout my entire PhD

research, reflected by the fact that he is a coauthor on all the five publications of mine. I would

also like to thank Shouming Zhou and Luis Ladino for being great mentors, as well as great friends

all the time; and Jenny Wong for helpful discussions about research and life throughout my

progress in graduate school. I would also like to extend my thanks to other current and past group

members, including Shawna Gao for editing my writing and teaching me how to operate PTR-MS

and TOC analyzer; Joel Corbin for teaching me tricks on Igor; Dana Aljawhary for offering a lot

of assistance on the ToF-CIMS; Nadine Borduas for all the exciting discussions into the depth of

organic chemistry; Richard Li for providing his great efforts on the UV-Vis measurements of

Brown Carbon; Emma Mungall for working together and shipping “sugar water” to Germany;

Rachel Chang and Rob McWhinney for being great senior students and mentors; Jacquie Yakobi

for being a cheerful neighbour and inviting Barbara Ervnes, my external-to-be to our lunch in the

conference; Rachel Hems for editing the introduction of this thesis; and Egda Escorcia, Jay Slowik,

Katie Badali, Maria Antonolo, Megan Willis, Julia Burkart, Cuyler Borrowman, Yasmine Katrib,

Katrina Macdonald, Bob Christensen, Appana Lok, Zack Finewax and Crystal Chen for being

great teammates.

A number of alumni / senior students both in and out of my research group have provided me with

enormous inspirations and helpful advice in making my decision for my future direction. This

includes Tara Kahan, Xianming Zhang, Jessica D’eon, Hashim Farooq, Sumi Wren, Rachel Chang,

and Jeff Geddes.

Finally, none of this would be possible without unconditioned love and encouragement from my

parents, Dong Zhao and Feng Jia, my grandfather, Guangshi Jia, my late grandmothers, Bianru Li,

Fangying Sheng, and the rest of family members. This is your achievement as much as mine.

vi

Table of Contents

Acknowledgments .......................................................................................................................... iv

Table of Contents ........................................................................................................................... vi

List of Tables ............................................................................................................................... xiii

List of Figures ............................................................................................................................... xv

List of Appendices .................................................................................................................... xxvii

Preface ...................................................................................................................................... xxviii

Chapter 1: Introduction to Aqueous-phase Organic Chemistry in the Atmosphere ....................... 1

1.1 Secondary Organic Aerosol and Its Environmental Impacts .............................................. 2

1.2 Formation Mechanisms of SOA ......................................................................................... 2

1.2.1 Gas-Particle Partitioning Theory – the Traditional Understanding of SOA

Formation ................................................................................................................ 2

1.2.2 Discrepancies between Models and Measurements ................................................ 3

1.2.3 Aqueous-phase Chemistry – a New Formation Mechanism of SOA ..................... 3

1.3 Atmospheric Aqueous Phases and Partitioning of Organic Compounds............................ 5

1.3.1 Aqueous Phases in the Atmosphere ........................................................................ 5

1.3.2 Partitioning of Organic Compounds to Aqueous Phase ......................................... 6

1.4 Production and Concentration of OH Radicals in Atmospheric Aqueous Phases .............. 9

1.4.1 Gas-Phase Partitioning and in-situ Formation of OH Radical ................................ 9

1.4.2 Mechanisms of in-situ Formation of OH Radical ................................................. 11

1.4.3 Diffuso-reactive Length (dL) of OH Radical ........................................................ 12

1.4.4 Steady State Concentrations of OH Radical ......................................................... 15

1.5 OH Reactivity and Reaction Mechanisms ........................................................................ 15

1.5.1 Initiation of the Radical Chain .............................................................................. 15

1.5.2 Propagation of Radical Chain ............................................................................... 17

vii

1.5.3 Termination of Radical Chain ............................................................................... 17

1.6 OH Radical Reactions Unique to the Aqueous Phase ...................................................... 17

1.6.1 Efficient Conversion of Aldehydes to Carboxylic Acids ..................................... 17

1.6.2 Rapid OH Oxidation of Carboxylate .................................................................... 19

1.6.3 Radical Induced Oligomerization ......................................................................... 20

1.6.4 Radical Induced Organosulfate Formation ........................................................... 21

1.7 Non-radical Chemistry in the Aqueous-phase – Nucleophilic Addition Reactions ......... 22

1.7.1 General Reaction Mechanism of Nucleophilic Addition ...................................... 22

1.7.2 Importance of Acid-catalysis ................................................................................ 23

1.7.3 Water Nucleophile and Hydration ........................................................................ 23

1.7.4 Alcohol Nucleophile and Hemiacetal Formation ................................................. 25

1.7.5 Enol Nucleophile and Aldol Condensation ........................................................... 25

1.7.6 Similarities and Differences in Hemiacetals and Aldol Condensates ................... 26

1.7.7 Hydroperoxide (ROOH) Nucleophile and Peroxyhemiacetal Formation ............. 26

1.7.8 Nitrogen-containing Nucleophiles and Atmospheric Brown Carbon Formation . 27

1.8 Removal of Organic Compounds in Aqueous-phase ........................................................ 28

1.9 Sampling and Measurement Techniques for Aqueous-phase Organic Compounds ......... 29

1.9.1 Sampling Techniques for Cloud and Fog Water ................................................... 29

1.9.2 Recent Development of Extraction and Measurement of Water Soluble

Organic Carbon Associated with Particles ........................................................... 30

1.9.3 Application of Online Mass Spectrometry to Aqueous-Phase Detection. ............ 31

1.10 Summary and Objectives .................................................................................................. 32

Bibliography ................................................................................................................................. 34

Chapter 2: Investigation of Aqueous-Phase Photooxidation of Glyoxal and Methylglyoxal by

Aerosol Chemical Ionization Mass Spectrometry: Observation of α-hydroxyhydroperoxide

Formation ................................................................................................................................. 53

Abstract .................................................................................................................................... 54

viii

2.1 Introduction ....................................................................................................................... 54

2.2 Experimental Methods ...................................................................................................... 57

2.2.1 Photooxidation of Aqueous Solution. ................................................................... 57

2.2.2 Aerosol CIMS ....................................................................................................... 59

2.2.3 Offline TOC and Complementary IC Analysis .................................................... 62

2.3 Results and Discussions .................................................................................................... 63

2.3.1 Formation of α-Hydroxyhydroperoxides (α-HHPs) in Dark Control

Experiments .......................................................................................................... 63

2.3.2 Photooxidation of GLY ......................................................................................... 66

2.3.3 Photooxidation of MG .......................................................................................... 68

2.3.4 TOC Concentration and Carbon Balance ............................................................. 71

2.3.5 Evidence of Oligomer Formation ......................................................................... 74

2.4 Conclusions ....................................................................................................................... 75

Acknowledgement .................................................................................................................... 77

Bibliography ............................................................................................................................. 77

Chapter 3: Aqueous-phase Photooxidation of Levoglucosan – a Mechanistic Study Using

Aerosol Time-of-Flight Chemical Ionization Mass Spectrometry (Aerosol ToF-CIMS) ....... 84

Abstract .................................................................................................................................... 85

3.1 Introduction ....................................................................................................................... 85

3.2 Experimental Methods ...................................................................................................... 87

3.2.1 Solution Preparation and Photooxidation ............................................................. 87

3.2.2 Aerosol-ToF-CIMS ............................................................................................... 88

3.2.3 Mechanistic and Kinetic Studies ........................................................................... 89

3.2.4 Aerosol Mass Spectrometry (AMS) Measurements ............................................. 90

3.3 Results and Discussion ..................................................................................................... 91

3.3.1 Reaction Products and Mechanism ....................................................................... 91

3.3.2 Kinetic Study ...................................................................................................... 102

ix

3.3.3 Comparison with AMS Data ............................................................................... 104

3.4 Conclusions and Environmental Implications ................................................................ 105

Acknowledgement .................................................................................................................. 107

Bibliography ........................................................................................................................... 107

Chapter 4: Formation of Aqueous-phase α-hydroxyhydroperoxides (α-HHP): Potential

Atmospheric Impacts ............................................................................................................. 113

Abstract .................................................................................................................................. 114

4.1 Introduction ..................................................................................................................... 114

4.2 Experimental Methods .................................................................................................... 118

4.2.1 1H NMR Measurements ...................................................................................... 118

4.2.2 Effects of Inorganic Salts .................................................................................... 120

4.2.3 PTR-MS Measurements ...................................................................................... 120

4.2.4 Reversibility Test: Addition of Catalase ............................................................. 121

4.3 Results and Discussion ................................................................................................... 121

4.3.1 1H NMR Results ................................................................................................. 121

4.3.2 PTR-MS Results ................................................................................................. 127

4.3.3 Comparison of Equilibrium Constants ................................................................ 128

4.3.4 Temperature Dependence of Kapp ....................................................................... 133

4.3.5 Effects of Inorganic Salt Addition ...................................................................... 135

4.4 Atmospheric Implications ............................................................................................... 136

4.4.1 Equilibrium concentrations of α-HHPs in cloud water and aerosol liquid water 136

4.4.2 Impact of α-HHP formation on the atmospheric partitioning of aldehydes and

H2O2 .................................................................................................................... 138

4.4.3 Other Atmospheric Implications ......................................................................... 140

4.5 Conclusions ..................................................................................................................... 142

Acknowledgement .................................................................................................................. 143

Bibliography ........................................................................................................................... 143

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Chapter 5: Photochemical Processing of Aqueous Atmospheric Brown Carbon ....................... 151

Abstract .................................................................................................................................. 152

5.1 Introduction ..................................................................................................................... 152

5.2 Methods ........................................................................................................................... 155

5.2.1 Preparation of BrC Solutions .............................................................................. 155

5.2.2 Direct Photolysis and OH Oxidation Experiments ............................................. 156

5.2.3 Direct Photolysis of WSOC from Biofuel Combustion ...................................... 158

5.3 Results and Discussion ................................................................................................... 158

5.3.1 Light Absorption of BrC ..................................................................................... 158

5.3.2 Imine BrC ............................................................................................................ 160

5.3.3 Nitrophenols ........................................................................................................ 164

5.3.4 Direct Photolysis of WSOC from Biofuel Combustion Samples ....................... 172

5.4 Conclusions and Atmospheric Implications ................................................................... 172

Acknowledgement .................................................................................................................. 173

Bibliography ........................................................................................................................... 174

Chapter 6: Cloud Partitioning of Isocyanic Acid (HNCO) and Evidence of Secondary Source

of HNCO in Ambient Air ....................................................................................................... 181

Abstract .................................................................................................................................. 182

6.1 Introduction ..................................................................................................................... 182

6.2 Methods ........................................................................................................................... 183

6.2.1 Site Description ................................................................................................... 183

6.2.2 Acid-CIMS .......................................................................................................... 184

6.2.3 CVI ...................................................................................................................... 184

6.3 Results and Discussion ................................................................................................... 185

6.3.1 Detection of HNCO From Cloudwater ............................................................... 185

6.3.2 Estimation of the Aqueous Fraction of HNCO (faq,HNCO) ................................... 186

xi

6.3.3 Unexpectedly High Aqueous Fraction of HNCO ............................................... 187

6.3.4 Evidence of a Secondary Source of HNCO in the Ambient Air ......................... 189

6.4 Summary ......................................................................................................................... 192

Acknowledgement .................................................................................................................. 193

Bibliography ........................................................................................................................... 193

Chapter 7: Conclusions and Future Research ............................................................................. 198

7.1 Summary and Future Research for Laboratory Investigations of Aqueous-phase

Chemistry ........................................................................................................................ 199

7.2 Summary and Future Research for Organic Hydroperoxide (ROOH) Formation .......... 200

7.3 Summary and Future Research for Atmospheric Brown Carbon (BrC) ......................... 201

7.4 Summary and Future Research for Cloud Partitioning of Organic Compounds ............ 202

Bibliography ........................................................................................................................... 203

Appendix A ................................................................................................................................. 206

A1 List of Detected Peaks .................................................................................................... 207

A2 Proposed Mechanisms .................................................................................................... 209

A3 Estimation of the Diffusion Limited Rate Constant of LG Oxidation by OH Radicals

in the Aqueous Phase. ..................................................................................................... 211

Bibliography ........................................................................................................................... 211

Appendix B ................................................................................................................................. 213

B1 Example 1H NMR Spectra and Peak Assignment for Each Carbonyl Compound. ........ 214

Bibliography ........................................................................................................................... 222

Appendix C ................................................................................................................................. 223

C1 Determination of Photon Flux in the Solar Simulator .................................................... 224

C2 Quantitative Assessment of BrC Absorption .................................................................. 225

C2.1 Imine BrC ............................................................................................................ 225

C2.2 WSOC from Biofuel Combustion Samples ........................................................ 226

C2.3 Nitrophenols ........................................................................................................ 226

xii

C3 Concentration Dependence of Imine BrC Decay Rate ................................................... 228

C4 Spectral Change of 4NP and 5NG during Direct Photolysis .......................................... 228

C5 pH Dependent Photo-enhancement of 4NP and 5NG and OH Scavenger Experiments 229

C6 pH Dependent Absorption of Nitrophenols .................................................................... 231

C7 Photooxidation of 4NP and 5NG .................................................................................... 231

C8 Simple Kinetic Model Applied to 4NP and 5NG ........................................................... 232

Bibliography ........................................................................................................................... 233

Appendix D ................................................................................................................................. 235

D1 Map of the measurement sites ......................................................................................... 236

D2 Calibration of the Acid-CIMS ........................................................................................ 236

D2.1 Calibration Methods ............................................................................................ 236

D2.2 Calibration factors and limits of quantification of HNCO and HNO3 ................ 236

D3 Quantification of HNCO and HNO3 in CVI. .................................................................. 237

D3.1 CVI Background ................................................................................................. 237

D3.2 Normalization and Quantification ....................................................................... 237

D4 Calculating the Aqueous Fraction of HNCO (faq,HNCO) .................................................. 238

D4.1 Determination of the Enhancement Factor (EF) ................................................. 239

D4.2 Determination of Droplet Transmission (DT) in the CVI .................................. 240

D4.3 Determination of the fraction of LWC sampled by CVI (fliquid) ......................... 241

D4.4 Error propagation for faq,HNCO ............................................................................. 241

D4.5 A sensitivity test for faq,HNCO ............................................................................... 242

D5 The pH-dependence of KHeff of HNCO and the theoretical aqueous fraction of HNCO

(faq,HNCO) .......................................................................................................................... 243

D6 Time series and diurnal profiles of HNCO, formic acid and ambient temperature ........ 244

D7 Strength of correlation between HNCO and BC during various time periods ............... 245

Bibliography ........................................................................................................................... 245

xiii

List of Tables

page

Table 1.1 Conditions used in the measurements of in-situ production rate of OH

radical.

11

Table 2.1 Experimental Conditions. 59

Table 3.1 Summary of the conditions and the results of the kinetic experiments. 102

Table 4.1 Summary of hydration equilibrium constants (Khyd) measured by NMR.

The constants are reported with their standard deviation arising from the

number of replicates indicated on the table.

125

Table 4.2 Summary of the apparent equilibrium constants of α-HHP formation

(Kapp) measured and reported in literature at 25 ˚C. The constants are

reported with their standard deviation acquired from the number of

replicates shown on the table.

126

Table 4.3 Temperature dependence of the apparent equilibrium constant (Kapp) of 1-

hydroxyethyl hydroperoxide (1-HEHP) formation from acetaldehyde.

134

Table 4.4 Effects of inorganic salt addition on the hydration equilibrium constant

(Khyd) and the apparent α-HHP formation equilibrium constant (Kapp).

135

Table 4.5 Conditions assumed in the atmospheric partitioning simulation of 1 ppb

of aldehydes or H2O2.

138

Table 4.6 Results of the atmospheric partitioning simulation. 141

Table 5.1 Estimated atmospheric half-life of Imine BrC arising in the glyoxal-

ammonium sulfate (GLYAS) and methylglyoxal-ammonium sulfate

(MGAS) solutions.

161

xiv

Table 5.2 Rate constants for photo-enhancement at 420 nm for 4-nitrocatechol

(4NC).

167

Table 5.3 Photo-enhancement and bleaching rate constants1 for nitrophenol OH

oxidation determined from a simple kinetic model (Section 5.3.3.2.).

170

Table 6.1 Summary of the Aqueous Fraction of HNCO (faq,HNCO) Measured and

Calculated.

188

Table A1 List of peaks detected by the I(H2O)n- reagent ion. The chemical formulae

were assigned using the data processing software (Tofwerk v. 2.2). The

peak time and Max. peak intensity are the illumination time at which each

peak reached its maximum, and its corresponding signal intensity at that

time, respectively. The peak intensity has been normalized by the

intensity of the reagent ion at m/z 145 (I(H2O)-). This information, along

with the exact m/z and mass defect were used to construct the mass defect

plot (Figure 3.4 in the main article). The compounds displayed in Figure

3.6 in the main article are color coded.

207

Table B1 Comparison of Kapp values experimentally determined and calculated as

(Keq/Kapp).

222

Table C1 The absorbance based 1st order rate constant of photo-enhancement. 230

Table D1 Calibration factors of the Acid CIMS. 236

Table D2 The parameters from the June 1st and the June 13th cloud events are

summarized. D50 represents the calculated 50 % size cutoff of the CVI

(the cloud droplet cut size).

238

Table D3 A comparison of the calculated faq,HNCO in the actual case and a perturbed

case. The perturbed values are highlighted in red.

242

xv

List of Figures

page

Figure 1.1 A schematic illustration of SOA formation via the gas-particle partitioning

theory and the aqueous pathway.

4

Figure 1.2 Calculated aqueous fraction (faq) at 298 K under three selected LWC as a

function of effective Henry’s law constant (Heff). The figure also shows Heff

values of selected compounds at 298 K, along with their molecular

structures. References: glyoxal (Ip et al. 2009), methylglyoxal (Zhou and

Mopper 1990), oxalic acid (pH 4) (Compernolle and Muller 2014), α-

pinene (Leng et al. 2013), toluene (Kim and Kim 2014), O3 (Gershenzon et

al. 2001) and NO2 (Chameides 1984).

8

Figure 1.3 Calculated gas-particle partitioning rates and measured in-situ formation

rates of OH radical as a function of particle diameter. The calculated rates

are based on three (1, 0.1 and 0.01) values of mass accommodation

coefficient (α), and the measured in-situ formation rates are compiled based

on a number of studies, with the conditions of which summarized in Table

1.1.

10

Figure 1.4 The diffuso-reactive length (dL) of OH as a function of dissolved organic

carbon (DOC) concentrations. The loss rate of OH radical is based on the

averaged, carbon based value reported in Arakaki et al. (2013). The

horizontal bars represents the approximate DOC ranges in a variety of

atmospheric aqueous phases.

13

Figure 1.5 Structures and OH reactivity (kIIOH, 298K) of organic compounds relevant

to atmospheric aqueous phases (Buxton et al. 1988, Herrmann 2003, Tan

et al. 2009, Herrmann et al. 2010, Tan et al. 2012).

14

Figure 1.6 General OH radical reactions. 16

Figure 1.7 Mechanisms of rapid carboxylic acid formation in the aqueous phase. 18

xvi

Figure 1.8 OH reactivity (kIIOH) of carboxylic acids and corresponding carboxylates.

Acronym: formic acid (FA), glyoxylic acid (GA), pyruvic acid (PA), lactic

acid (LA), malic acid (MA), oxalic acid (OA). References: FA, GA and OA

(Tan et al. 2009), PA (Schaefer et al. 2012), LA and MA (Herrmann et al.

2010).

19

Figure 1.9 Charge transfer reaction of carboxylate. 20

Figure 1.10 Radical induced oligomerization mechanism, with one example each for

radical-radical recombination (a) (Guzman et al. 2006, Lim et al. 2010) and

radical propagation on double bonds (b) (Renard et al. 2013).

21

Figure 1.11 Nucleophilic addition reactions associated with carbonyl compounds. 24

Figure 2.1 Simplified reaction mechanisms of aqueous-phase photooxidation of GLY

(Lim et al. 2010) and MG (Lim et al. 2005, Altieri et al. 2008). The two-

way arrows represent reversible processes, whereas the one-way arrows

represent irreversible OH oxidation.

56

Figure 2.2 Schematic description of Aerosol CIMS and photooxidation cell. 58

Figure 2.3 Pathways showing formation of α-hydroxyhydroperoxides. 63

Figure 2.4 Formation of α-HHPs in dark control experiments. H2O2 (13 mM) was

added to 3 mM of GLY (a) or 3 mM of MG (b) solutions at time (I), and

quenched at time (II) by addition of catalase from bovine liver. α-HHPs

formed sharply after the addition of H2O2 and reached equilibrium values

approximately 40 min after the addition. After quenching of H2O2, α-HHPs

decayed to zero and reversibly formed GLY or MG.

64

Figure 2.5 Results of photooxidation experiments with 3 mM (a) and 0.3 mM (b)

initial GLY concentration. Photooxidation was initiated at time 0 (dashed

line). Data shown here are the average of 2−3 replicates, and the error bars

represent fluctuations between replicates (1 σ). The signal of 2-hydroxy-2-

66

xvii

hydroperoxyethanal (HHPE) overlaps with that of hydrated GA

(GA·1H2O). This normalized signal from one typical experiment is shown

(right axis).

Figure 2.6 Possible formation mechanisms of formic and acetic acids from α-HHPs

(from da Silva (2011)).

67

Figure 2.7 Three mM GLY photooxidation without α-HHP equilibrium. The

experiment was conducted as with the 3 mM GLY photooxidation, except

that photooxidation was initiated immediately after H2O2 was added to the

GLY solution at time 0. The error bars represent fluctuations between

replicates (1 σ).

68

Figure 2.8 Concentration profiles of MG and its products. Photooxidation was

initiated at time 0 (dashed line). The oxalic acid profile obtained from IC

and its fitted line are shown on the graph. Using the fitted line, the MG

concentration profile was calculated. The data represent the average of two

independent replicates, with the error bars showing fluctuation between the

replicates (1 σ). The normalized signal of 2-hydroxy-2-

hydroperoxypropanal (HHPP) and hydroxyhydroperoxyacetone (HHPA)

from one experiment is shown (right axis).

69

Figure 2.9 H2O2 control experiment for MG. MG solution (3 mM) was exposed to

irradiation without addition of H2O2. The irradiation was initiated at time 0

(dashed line). A significant amount of FA and AA was produced. The initial

increase of the MG signal was due to equilibration of MG in the inlet line,

and the initial signal of FA and AA are due to impurities in solution or due

to decomposition of MG prior to the experiment.

70

Figure 2.10 Normalized signal of OA (blue) was obtained from the fitted line of IC data.

The normalized signal of MG (yellow) was calculated by subtracting OA

normalized signal from total signal of MG + OA (black) obtained from the

Aerosol CIMS.

71

xviii

Figure 2.11 Measured and reconstructed TOC concentration in 3 mM glyoxal (GLY)

(a), 0.3 mM GLY (b), and 3 mM methylglyoxal (MG) photooxidation

experiments. Photooxidation was initiated at time 0 (dashed line). The

measured TOC shows the results from the offline TOC analyzer whereas

the reconstructed TOC is calculated from the total of the quantified organic

species (i.e., excluding α-HHPs and oligomers); see text. CIMS data

represent the average of 2−3 independent experimental replicates, and the

error bars represent fluctuations between the replicates (1 σ).

72

Figure 2.12 Decay time profiles of GLY·1H2O and GLY·2H2O during one typical

photooxidation experiment. The α-HHP equilibrium was fully established

before the photooxidation was initiated at time 0 (dashed line).

73

Figure 2.13 Formation of MA and SA in 3 mM GLY photooxidation. 75

Figure 3.1 The experimental apparatus. 88

Figure 3.2 The evolution of the “+O” (a) and the “−2H” (b) series from levoglucosan

(LG). The signal of each compound normalized by the reagent ion intensity

at m/z 145 (I(H2O)−) is shown as a function of the irradiation time. The

signals are multiplied by the bracketed number to be on scale.

92

Figure 3.3 The mass defect diagram of the major products detected using the iodide

water cluster (I(H2O)−n) reagent ion (a). The color code indicates the time

at which each compound reached its maximum signal intensity and the area

of the circles represents the maximum signal intensity reached (in log

scale). Compounds that did not reach their maxima during the first 300min

of illumination are shown in black. The +O and the −2H series fall on the

slope indicated by the dotted lines. The region relevant to products arising

from +O and −2H trends is presented in (b). The proposed structures of

each product are shown beside the data points.

93

Figure 3.4 Sample reaction mechanisms that give rise to the +O and −2H trends. The

tetroxide intermediate forming from two alkylperoxy radicals can result in

94

xix

a variety of products as shown in (R3.1) to (R3.3), among which (R3.1) can

lead to formation of the hydroxyl functional group. A hydroperoxy

functional group can be formed from RO2 +HO2 (R3.4). The hydroxyl-to-

carbonyl conversion shown in (R3.5) is likely responsible for the −2H

trend. Alkoxy radicals trigger bond-scission reactions and give rise to an

aldehydic compound (R3.6).

Figure 3.5 Evolution of bond-scission products measured by the I(H2O)−n reagent ion.

Selected major products with three to six carbons are shown in (a), with

their proposed structures. The proposed reaction mechanisms leading to

their formation are attached in Appendix A Figure. A1. Formation of small

organic acids with one or two carbons are shown in (b). All the signals have

been normalized against the reagent ion (I(H2O)−) at m/z 145.

96

Figure 3.6 Intensity-weighted average of double bond equivalence (DBE), DBE-to-

carbon ratio (DBE/#C), and oxidation state (OSc) as a function of

irradiation time.

99

Figure 3.7 OSc vs DBE/#C plot. The intensity-weighted average OSc and DBE/#C

from the products listed in Appendix A Table A1 are displayed here. The

color code represents the illumination time. The coordinates of major

compounds are also shown.

100

Figure 3.8 A simplified overview of reaction mechanisms discussed in the current

study. Solid arrows represent proposed reaction pathways of LG upon OH

oxidation. The dashed arrows illustrate the complicity in the reaction

system where each product can also take more than one reaction path.

101

Figure 3.9 The time series of LG and DMSO during a kinetic experiment (Exp. #1 in

Table 3.1) are shown in (a). The signals are normalized to those at the

beginning of the photooxidation. The relative kinetics plot from the same

experiment is shown in (b) according to Eqn. 3.1. The color code indicates

the illumination time.

103

xx

Figure 3.10 The decay of levoglucosan monitored by the Aerosol ToF-CIMS and the

decay of f60 monitored by the AMS (a), and the f60 vs. f40 trajectory from

the current work compared to field measurements (b). The trajectory

obtained in the current work is color coded with irradiation time. The

compiled data (Cubison et al., 2011) from field measurements in fire

plumes (grey) and non-fire plumes (brown) are also shown.

105

Figure 4.1 Two aqueous-phase pathways of α-hydroxyhydroperoxide (α-HHP)

formation: 1) The Criegee Pathway, 2) the Carbonyl pathway, and a related

reaction 3) Peroxyhemiacetal formation.

117

Figure 4.2 Experimental setup for the PTR-MS measurements. 120

Figure 4.3 1H NMR spectra for acetaldehyde. (a): Acetaldehyde aqueous solution; (b):

17.7 mM of H2O2 was added to the acetaldehyde solution; (c): Catalase was

added to the solution to quench H2O2. The insets are the magnified view of

certain regions of the spectra. The split pattern and the identity of each peak

are shown in the brackets (the numbers match those in the chemical

structures).

122

Figure 4.4 Hydration equilibrium constant (Khyd), the α-HHP formation equilibrium

constant (Keq) and the apparent α-HHP formation equilibrium constant

(Kapp). Please see the text for details.

123

Figure 4.5 Sample time series of signal due to gas-phase acetaldehyde in the PTR-MS

experiment. The acetaldehyde signal normalized to the reagent ion is shown

as a function of time. Time (i): 25 mL of clean water in the bubbler is

replaced by 25 mL of acetaldehyde solution (10 mM), Time (ii): 13.3 mM

of H2O2 is added to the acetaldehyde solution, Time (iii): one drop of

catalase stock solution is added.

127

Figure 4.6 1H NMR spectra of a formaldehyde-H2O2 mixture. The splitting pattern and

assignment of the peaks are shown in the bracket.

130

xxi

Figure 4.7 Typical acetaldehyde time profiles at 5, 15 and 25 ˚C are shown in (a). The

ratios of signal at a given time to the initial signal are shown. H2O2 (13.3

mM) was injected to the 10 mM acetaldehyde solutions at time (i). The

dashed lines show the signal levels at equilibrium. The van’t Hoff diagram

for 1-hydroxyethyl hydroperoxide (1-HEHP) formation from acetaldehyde

is shown in (b). The dashed lines connects +1 σ and -1 σ from the average

ln(Kapp) determined at the three temperatures.

134

Figure 4.8 Simulation of the equilibrium concentration of α-hydroxyhydroperoxide

([α-HHP]eq) arising from various equilibrium concentrations of H2O2

([H2O2]eq) and total aldehyde ([Total Aldehyde]eq). The concentrations are

all presented in log scale. Conditions relevant to cloud water and aerosol

water are also indicated. This simulation considers α-HHP formation via

only the Carbonyl Pathway, with an average equilibrium constant of 100

M-1.

137

Figure 5.1 Experimental procedures. 156

Figure 5.2 Absorption spectra of BrC investigated in this study (a) and WSOC from

the biofuel combustion samples (b). The y-axis in (a) is in arbitrary units to

keep the absorbance of all the solutions on scale.

159

Figure 5.3 Spectral change of the MGAS solution during a direct photolysis

experiment (a) and the absorbance change at 400 nm as a function of

illumination time (b). The inset in (b) shows the 1st order plot of the decay,

and the lines are linear least square plots forced through the origin. The

shaded area represent the range obtained from 3 replicates.

161

Figure 5.4 Time profiles of absorbance at 400 nm during OH oxidation (solid lines)

and H2O2 control (dashed lines) experiments. Results for both the GLYAS

(blue traces) and the MGAS (red traces) solutions are shown. The decay

profiles of absorbance at 400 nm normalized to the initial value at t =0 are

162

xxii

shown in (a), while their corresponding 1st order decay plots are shown in

(b).

Figure 5.5 Proposed explanation for the difference in the major bleaching processes

of the GLYAS and the MGAS solutions.

164

Figure 5.6 Spectral change of a 4NC solution (4 µM) during a direct photolysis

experiment. The inset shows the absorbance change compared to the initial

condition.

165

Figure 5.7 Time profiles of 4NC absorbance at 420 nm during direct photolysis

experiments. Experiments were performed at three solution pH values. An

OH scavenger experiment was also performed by adding 1 mM glyoxal to

the pH 5 solution.

166

Figure 5.8 Spectral change of 4NC solution (10 µM) during an OH oxidation

experiment (a), with the inset showing absorbance change compared to the

initial condition. The color coding represents the illumination time. The

time profiles of absorbance at 420 nm are shown in (b). The black trace is

from a H2O2 control experiment, while the red trace is from one of the OH

oxidation experiments.

168

Figure 5.9 A schematic illustration of the simple kinetic model (a) and one example

of 4NC photooxidation (b). The shaded areas in (b) are the contributions

from a newly formed colored product (CP) and the decaying 4NC,

respectively. The red line follows data from an experiment.

170

Figure 5.10 Direct photolysis of the WSOC from biofuel combustion samples. The

spectral evolution of the kaoliang and the cotton samples is shown in (a)

and (b), respectively. The color code indicates illumination time, while the

insets show the absorbance change compared to the initial condition. The

time profiles of absorbance at three different wavelengths for the same

samples are shown in (c) and (d), respectively.

171

xxiii

Figure 6.1 Time series of HNCO and HNO3 mixing ratios measured after the CVI

during (a) the June 1st event and (b) the June 13th event are shown along

with LWC in the surrounding air. (c) The correlations of HNCO with LWC

for both of the events are shown.

186

Figure 6.2 The time profile of HNCO and HNO3 measured during a selected period of

(a) the campaign and (b) the averaged diurnal profiles of HNCO, HNO3,

and black carbon (BC) from the entire campaign, where the error bars

represent 1𝜎 of the diurnal variation. (c) The primary-secondary

apportionment of HNCO is shown. See text for details about the

apportionment.

190

Figure 6.3 The time profile of HNCO and HNO3 measured during a selected period of

(a) the campaign and (b) the averaged diurnal profiles of HNCO, HNO3,

and black carbon (BC) from the entire campaign, where the error bars

represent 1𝜎 of the diurnal variation. (c) The primary-secondary

apportionment of HNCO is shown. See text for details about the

apportionment.

192

Figure 7.1 Calculated aqueous fraction (faq) as a function of effective Henry’s law

constant Heff. The figure is same as Figure 1.2, but with the addition of faq

at bulk LWC (106 g m-3) where chemicals exist entirely in the aqueous phase.

200

Figure A1 Proposed reaction mechanism giving rise to the products displayed in

Figure 3.6 (main article). The overall reaction mechanism of levoglucosan

photooxidation is highly complicated, and only a subset is shown here. As

one example, the mechanism demonstrates the case when H-abstraction

occurs at the position shown in Scheme 1. Subsequent chain scission can

lead to two different reaction pathways shown in Scheme 2 and Scheme 3,

respectively. Scheme 4 demonstrates that products from Scheme 3 can

undergo the hydroxyl-to-carbonyl conversion which is discussed in the

functionalization section in the main article. Scheme 5 illustrates hydration

of an aldehyde and its subsequent conversion to a carboxylic acid.

210

xxiv

Figure B1 Glycolaldehyde (10 mM) and H2O2 (17.7 mM). 214

Figure B2 Methylglyoxal (10 mM) and H2O2 (17.7 mM). 215

Figure B3 Propionaldehyde (10 mM) and H2O2 (17.7 mM). 216

Figure B4 Glyoxal (10 mM) and H2O2 (17.7 mM). 217

Figure B5 Glyoxylic acid (10 mM) and H2O2 (17.7 mM). 218

Figure B6 Methacrolein (10 mM) and H2O2 (100 mM). 219

Figure B7 Methylethyl ketone(10 mM) and H2O2 (100 mM). 220

Figure B8 Acetone (10 mM) and H2O2 (100 mM). 221

Figure C1 The photon flux in the solar simulator and in the ambient. 225

Figure C2 Wavelength dependent mass absorption coefficient (MAC) for the Imine

BrC (a), the WSOC from biofuel combustion samples (b), and the base 10

absorption cross section and molar absorptivity of the nitrophenols (c).

227

Figure C3 Decay of the GLYAS solution (a) and the MGAS solution (b) during the

first 10 min of illumination at different initial concentrations.

228

Figure C4 Spectral change observed for a 4NP solution (a) and a 5NG solution (b)

during direct photolysis experiments. The initial concentrations of 4NP and

5NG were 5 µM and 4 µM, respectively. The insets illustrate the

absorbance change compared to the initial conditions.

228

Figure C5 Color formation from 4NP and 5NG solutions during the pH dependent and

the OH scavenger experiments. The formation profiles of absorbance at 420

nm and 450 nm from 4NP are shown in (a) and (b). The formation profiles

of absorbance at 420 nm from 5NG are shown in (c).

230

Figure C6 Absorption spectra of 4NP (a), 5NG (b) and 4NC (c) at various solution pH

values.

231

xxv

Figure C7 The spectral change of 4NP and 5NG solutions during OH oxidation

experiments are shown in (a) and (c). The time profiles of absorbance at

420 nm for 4NP and 5NG are shown in (b) and (d). In (b) and (d), the black

traces represent H2O2 control experiments, while the red traces represent

OH oxidation experiments. The concentration of 4NP and 5NG solutions

are 15 µM and 8 µM, respectively.

232

Figure C8 The simple kinetic model applied to one example experiment each of 4NP

(a) and 5NG (b) OH oxidation. The shaded areas are the simulated

contribution of a newly formed colored product and the decay precursor.

The red lines represent the experimental results.

233

Figure D1 The current work was part of a collaborative field measurement at La Jolla,

CA. Measurements were performed concurrently at two locations: Mt.

Soledad (A), and Scripps Pier (B). The current paper focuses on the CIMS

data obtained at site A.

236

Figure D2 Calculated time series of the aqueous-fraction of HNCO (faq,HNCO) during

the June 1st and June 13th cloud events.

239

Figure D3 Comparison of number concentrations of cloud droplets in the ambient air

(Ndroplet >D50), and evaporation residue in the CVI (NRes) divided by the

calculated EF. Data from the June 1st event (a) and the June 13th event (b)

are shown. The dashed line represents a line with a slope of one, whereas

the solid line shows the actual linear fitting. Droplet Transmission (DT) is

obtained as the reciprocal of the slope.

240

Figure D4 The size distribution of number (black), volume (blue) and surface area

(green) concentration of cloud droplets in the ambient air during the June

1st (a) and the June 13th (b) events, monitored by the Fog Monitor. The

dashed lines represent calculated 50 % size cut-off of the CVI.

241

Figure D5 Calculated KHeff of HNCO as a function of pH, based on data reported by

[Roberts et al., 2011] is shown in (a). The measured pH of bulk cloud water

243

xxvi

samples collected during the June 1st Event (Blue) and the June 13th Event

(red) are also shown as the dashed lines. The KHeff at these two pH values

are 3.0 × 103 and 8.0 × 102 M atm-1, respectively. Based on the KHeff values

shown on (a), the theoretical aqueous fraction of HNCO (faq,HNCO) is

calculated as a function of pH and LWC (b).The calculations assume

complete Henry’s law equilibrium between the gas and aqueous phases.

Figure D6 Time series of HNCO, formic acid and ambient temperature during a

specific period of the campaign are shown in (a). Clear correlations

between these traces can be seen. The campaign-averaged diurnal profiles

are shown in (b). The peak of HNCO mixing ratio is reached at similar time

as the other traces shown here.

244

Figure D7 Linear fitting between HNCO and Black Carbon (BC) was performed for

various time periods of each measurement day, and R2 values from the

fitting are shown here. The correlation is typically strongest during morning

rush hours (5am to 8am; black). The differences are statistically significant

at the 95% confidence level. This is an indication that there might be a

primary source of HNCO during the morning rush hour.

245

xxvii

List of Appendices

Page

Appendix A Supplementary information for Chapter 3. 206

Appendix B Supplementary information for Chapter 4. 213

Appendix C Supplementary information for Chapter 5. 223

Appendix D Supplementary information for Chapter 6. 235

xxviii

Preface

This thesis is based on manuscripts that have been published in or are in preparation for submission

for publication in peer reviewed journals. Consequently there may be some overlap in material that

is presented throughout the thesis. All manuscripts included in this thesis were written by Ran

Zhao, with critical comments provided by Jonathan P. D. Abbatt. Contributions of any other

authors are described below.

Chapter 1: Introduction to Aqueous-phase Organic Chemistry in the Atmosphere

Contributions: Written by Ran Zhao with critical comments from Jonathan P. D. Abbatt.

Chapter 2: Investigation of Aqueous-Phase Photooxidation of Glyoxal and

Methylglyoxal by Aerosol Chemical Ionization Mass Spectrometry:

Observation of α-hydroxyhydroperoxide Formation

Published as: R. Zhao, A.K.Y. Lee and J.P.D. Abbatt (2012). “Investigation of Aqueous-

Phase Photooxidation of Glyoxal and Methylglyoxal by Aerosol Chemical

Ionization Mass Spectrometry: Observation of Hydroxyhydroperoxide

Formation" Journal of Physical Chemistry A 116(24): 6253-6263

Contributions: The experimental approach was developed by Ran Zhao. All experiments

described in this section were performed by Ran Zhao. The manuscript was

written by Ran Zhao with critical comments from Alex K. Y. Lee and

Jonathan P. D. Abbatt.

Chapter 3: Aqueous-phase Photooxidation of Levoglucosan – a Mechanistic Study

Using Aerosol Time-of-Flight Chemical Ionization Mass Spectrometry

(Aerosol ToF-CIMS)

xxix

Published as: R. Zhao, E.L. Mungall, A.K.Y. Lee, D. Aljawhary and J.P.D. Abbatt

(2014). “Aqueous-Phase Photooxidation of Levoglucosan: A Kinetic and

Mechanistic Study Using High Resolution Aerosol Chemical Ionization

Mass Spectrometry (HR-Aerosol-CIMS)." Atmospheric Chemistry and

Physics, 14, 9695-9706.

Contributions: The experimental approach was developed by Ran Zhao. All experiments

using chemical ionization mass spectrometry (CIMS) described in this

section were performed by Ran Zhao and Emma L. Mungall, under the

guidance of Ran Zhao. The operation and data analysis of aerosol mass

spectrometry was done by Alex K. Y. Lee. The initial optimization of the

CIMS was performed by Dana Aljawhary. The manuscript was written by

Ran Zhao with critical comments from Jonathan P. D. Abbatt.

Chapter 4: Formation of Aqueous-phase α-hydroxyhydroperoxides (α-HHP):

Potential Atmospheric Impacts

Published as: R. Zhao, A.K.Y. Lee, R. Soong, A.J. Simpson and J.P.D. Abbatt (2013).

“Formation of Aqueous-Phase α-Hydroxyhydroperoxides (α-HHP):

Potential Atmospheric Impacts." Atmospheric Chemistry and Physics, 13,

5857-5872.

Contributions: The experimental approach was developed by Ran Zhao. All experiments

described in this section were performed by Ran Zhao and Alex K.Y. Lee.

The operation and data analysis of nuclear magnetic resonance (NMR)

spectrometry were conducted under the guidance of Ronald Soong and

Andre J. Simpson. The manuscript was written by Ran Zhao with critical

comments from Jonathan P. D. Abbatt.

Chapter 5: Photochemical Processing of Aqueous Atmospheric Brown Carbon

xxx

Published as: R. Zhao, A.K.Y. Lee, L. Huang, X. Li, F. Yang and J.P.D. Abbatt (2015).

“Photochemical processing of aqueous atmospheric brown carbon"

Atmospheric Chemistry and Physics Discussion 15, 2957-2996

Contributions: The experimental approach was developed by Ran Zhao. All experiments

described in this section were performed by Ran Zhao. The initial setup and

optimization of the waveguide capillary cell UV-Vis spectrophotometer

was performed by Alex K. Y. Lee. The collection and preparation of the

biofuel combustion samples were performed by Lin Huang, Xinghua Li and

Fumo Yang. The manuscript was written by Ran Zhao with critical

comments from Jonathan P. D. Abbatt.

Chapter 6: Cloud Partitioning of Isocyanic Acid (HNCO) and Evidence of

Secondary Source of HNCO in Ambient Air

Published as: R. Zhao, A.K.Y. Lee, J. Liggio, J.J.B. Wentzell, R.W. Leaitch, A.M.

Mcdonald, D. Toom-Sauntry, R.L. Modini, A.L. Corrigan, L.M. Russell,

K.J. Noone, J.C. Schroder, A.K. Bertram, L.N. Hawkins and J.P.D. Abbatt

(2014). “Cloud Partitioning of Isocyanic Acid (HNCO) and Evidence of

Secondary Source of HNCO in Ambient Air" Geophysical Research Letter

41, 6962-6969

Contributions: The overall plan for the field measurement was made by Richard W.

Leaitch, John Liggio, Lynn M. Russell and coworkers at Environment

Canada. The initial preparation of the sampling site was conducted by Rob

L. Modini, Ashley L. Corrigan, Lynn M. Russell and her research group.

Operation of the CIMS was done by Ran Zhao, Alex K. Y. Lee, Jeremy J.

B. Wentzell and John Liggio. The analysis of the CIMS data was conducted

by Ran Zhao. The operation and data analysis for Black Carbon

measurements were conducted by Jason C. Schroder and Allan K. Bertram.

The O3 data was obtained and processed by Anne Marie Mcdonald. The

xxxi

development of the counterflow virtual impactor (CVI) was done by Kevin

J. Noone. The operation of the CVI was conducted collaboratively by all

the coworkers mentioned above. The data analysis of CVI was conducted

by Jason C. Schroder. The manuscript was written by Ran Zhao with

critical comments from Jonathan P. D. Abbatt.

Chapter 7: Conclusions and Future Research

Contributions: Written by Ran Zhao with critical comments from Jonathan P. D. Abbatt.

1

Chapter 1

Introduction to Aqueous-phase Organic Chemistry in the Atmosphere

2

1.1 Secondary Organic Aerosol and Its Environmental Impacts

Aerosol refers to suspended particulate matter in the atmosphere and plays an important role in

two critical and urgent issues: air quality and global climate change. The connection between

adverse health effects and air pollution has been well established (Dockery et al. 1993), and

particulate matter, in particular, causes increased risk of a variety of cardiovascular diseases (Pope

et al. 2002). Aerosol affects the global climate by interacting with incoming solar radiation (the

direct radiative effect) and affecting the formation and lifetime of clouds (the indirect radiative

effects). Organic particulate matter forming in the atmosphere from precursor volatile organic

compounds (VOCs) is referred to as secondary organic aerosol (SOA) and comprises a substantial

fraction of submicron particulate matter (Zhang et al. 2007). Understanding the formation and

evolution of organic matter represents an essential step towards a sound assessment of the

environmental impact of aerosol. However, the complexity of the atmospheric chemical matrix

and its chemistry place major limitations on our ability to predict the amount and impact of SOA

in the atmosphere. Consequently, aerosol bears the single largest uncertainty in its radiative forcing

among that of all atmospheric drivers (Stocker et al. 2013).

1.2 Formation Mechanisms of SOA

1.2.1 Gas-Particle Partitioning Theory – the Traditional Understanding of SOA Formation

As the atmosphere is an oxidizing environment, the precursor VOCs are oxidized in the gas phase

and form more functionalized and oxygenated compounds which are categorized as semi-volatile

or non-volatile organic compounds. Additional functional groups on a molecule reduce the

molecular vapor pressure by orders of magnitude (Kroll and Seinfeld 2008) and induce partitioning

to the condensed phase to form SOA. The formation of SOA has been described by the gas-particle

partitioning theory (Odum et al. 1996, Pankow 1994). In this traditional view of SOA formation,

chemical reactions occur only in the gas-phase, with the semi-volatile products partitioning

between the gas and the condensed organic phases. The gas-particle partitioning is assumed to be

an equilibrium process, controlled by the saturation vapor pressures of the partitioning compounds,

the concentrations of the partitioning compounds in the gas and the condensed phases, the size of

the condensed organic phase, and the activity coefficient of the compounds in the condensed phase.

3

Partitioning of gas-phase organic compounds is considered to occur only to a pure organic

condensed phase, and contributions of aqueous phase and inorganic components are neglected.

1.2.2 Discrepancies between Models and Measurements

Studies from a decade ago found that models based on the traditional gas-particle partitioning

theory could not reproduce certain aspects of ambient aerosol, indicating unrecognized SOA

formation mechanisms or precursors. The first aspect is the SOA mass, which is significantly

underestimated in the models. Volkamer et al. (2006) have shown that this underestimation has

been observed in multiple field campaigns, with the gap widening as the locations of the

measurement are further away from the emission source. The ambient SOA mass can be up to a

hundred times of that modelled in the free troposphere (Heald et al. 2005).

The model prediction of SOA was significantly improved later by a volatility basis set approach,

where organic compounds are lumped into prescribed logarithmic volatility bins (Donahue et al.

2006). The VBS captures SOA formation from semi-volatile organic compounds which were

neglected in the traditional two-product model (Robinson et al. 2009). While the VBS improved

the prediction of SOA mass (Hodzic et al. 2010), it still fails in reproducing other aspects of SOA,

such as the O/C ratio and the formation of oligomeric compounds.

A substantial amount of oligomeric compounds exist in ambient and chamber-generated SOA

(Kalberer et al. 2004, Graber and Rudich 2006). These compounds, highly functionalized and

unresolved, are also referred to as Humic-like substances (HULIS) due to their spectral similarities

to humic acid (Graber and Rudich 2006). While the term oligomer strictly refers to a molecule

with a few repeating monomer unites, it is often used in the SOA community as molecule with

large molecular weight. The formation of oligomeric compounds cannot be explained by the

traditional view of gas-particle partitioning theory, as oligomerization reactions in the gas phase

are unlikely. Alternatively, atmospheric aqueous phases (cloud, fog, and aerosol liquid water) have

emerged as important reaction media where highly functionalized and oligomeric compounds can

form.

1.2.3 Aqueous-phase Chemistry – a New Formation Mechanism of SOA

Cloudwater has long been known as an important reaction medium in the atmosphere. Motivated

by endeavors to understand acid rain formation, detailed investigations have been performed for

4

inorganic chemistry, particularly that associated with sulfate formation in cloudwater (Chameides

1984, Jacob 1986, Pandis and Seinfeld 1989). Although the abundance of organic compounds in

atmospheric aqueous phases has been realized, the investigations have been limited to chemistry

of a small group of species. Formaldehyde is the most thoroughly studied organic compound

because its chemistry in cloudwater affects sulfate formation (Olson and Hoffmann 1989) and the

budget of HOx (i.e. OH and HO2 radicals) and O3 in the gas phase (Lelieveld and Crutzen 1991).

Figure 1.1: A schematic illustration of SOA formation via the gas-particle partitioning theory and the aqueous

pathway.

Blando and Turpin (2000) for the first time hypothesized that organic chemistry in cloudwater can

give rise to SOA components, and that a wide variety of organic compounds, including small

carbonyls, organic hydroperoxides and carboxylic acids, can be potential SOA precursors. These

compounds are not considered as SOA precursors by the traditional gas-particle partitioning

theory, given their small molecular weight and high vapor pressure. However, these compounds

are highly functionalized and hydrophilic, hence they can readily dissolve into atmospheric

aqueous phases. Numerous studies from the past decade have confirmed that aqueous-phase

reactions of these compounds indeed give rise to non-volatile products which contribute to SOA

upon water evaporation (Ervens et al. 2011, McNeill 2015). Thus, aqueous chemistry, also referred

5

to as aqueous-phase processing of organic compounds, represents an unrecognized formation

pathway of SOA involving unrecognized precursors. The overall processes involved in the

aqueous pathway of SOA formation are schematically illustrated in Figure 1.1, along with those

of the traditional gas-particle partitioning theory. The detailed aqueous-phase chemistry

contributing to aqueous SOA formation will be discussed in Sections 1.5 to 1.7.

1.3 Atmospheric Aqueous Phases and Partitioning of Organic Compounds.

1.3.1 Aqueous Phases in the Atmosphere

Liquid water is ubiquitous in the atmosphere, forming aqueous phases with highly diverse

characteristics. Liquid water is associated with most types of particulate matter, referred to as

aerosol liquid water (ALW). Under sub-saturated conditions (RH < 100 %), the uptake of water in

a particle is an equilibrium process, with ALW expanding with increasing RH. In the case of a

liquid particle, the growth of the particle as a function of RH follows its hygroscopic growth curve

(Finlayson-Pitts and Pitts 2000). Particles of inorganic salts remain solid at low RH values and

rapidly undergo deliquescence into liquid particles at their deliquescence RH. After deliquescence,

the particle grows continuously as the RH further increases. The specific deliquescence RH and

growth curve of a particle depend and the hygroscopicity of its chemical components. Hygroscopic

growth can increase the diameter of a particle up to a factor of 3 as the RH reaches 100 %

(Finlayson-Pitts and Pitts 2000), resulting in a typical liquid water content (LWC) of up to 10 µg

m-3 in the ambient atmosphere (Volkamer et al. 2009), but can be much higher under polluted

conditions (Bian et al. 2014).

Under supersaturated conditions (i.e. RH > 100 %), the uptake of water remains an equilibrium

process until the RH reaches the critical supersaturation or the particle grows to reach its critical

radius. At this point, the particle will continue taking up water and growing into a fog or cloud

droplet. The critical supersaturation and radius for a given particle are controlled by its size and

the hygroscopicity of its chemical components (Wong et al. 2011). The process of a particle

growing to a droplet is referred to as activation and is accompanied by orders of magnitude increase

in LWC, with typical LWC in cloud and fog being 0.1 to 1 g m-3 (Volkamer et al. 2009).

6

While continuous growth of cloud droplets leads to precipitation, only 10 % of the droplets actually

precipitate, with the majority evaporating and regenerating a particle (Seinfeld and Pandis 2006).

Thus a particle undergoes repeated activation and evaporation cycles before it is removed from the

atmosphere. Cloud/fog water and ALW are usually considered as two distinct reaction media due

to their differences in droplet size, LWC, salinity and surface area to volume ratio (Volkamer et

al. 2009, Ervens and Volkamer 2010, Lim et al. 2010, Ervens et al. 2011). Both ALW and

cloud/fog water are important for aqueous-phase chemistry involved in SOA formation (Figure

1.1). More recent studies have shown that chemical reactions can occur also during the process of

droplet evaporation (De Haan et al. 2011, Zarzana et al. 2012, Galloway et al. 2014).

1.3.2 Partitioning of Organic Compounds to Aqueous Phase

As described in Section 1.2.3, important aqueous SOA precursors can be highly functionalized

compounds with relatively small molecular weight. Since these compounds exhibit high vapor

pressure, they are introduced into atmospheric aqueous phases via gas-aqueous phase partitioning.

The gas-aqueous equilibrium of a compound is described by its Henry’s law constant, expressed

as the ratio of its aqueous-phase concentration and gas-phase vapor pressure (M atm-1). If a

compound undergoes equilibrium reactions in the aqueous phase, e.g. acid dissociation for acidic

compounds and hydration reactions for aldehydes, the Henry’s law constant of this compound

appears to be enhanced. The gas-aqueous equilibria of such compounds are described instead by

their effective Henry’s constants (Heff) which consider the additional aqueous-phase processes.

Strictly, Heff describes the enhanced partitioning of a compounds in ideal solutions without further

chemical transformation (i.e. the enhancement is only due to hydration and acid-dissociation

equilibria). However, we note that Heff is used here as the enhanced Henry’s law constant as a

result of all kinds of chemical equilibria occurring in the aqueous phase. Heff of a compound can

be orders of magnitude higher than its intrinsic Henry’s law constant, as represented by the case

of glyoxal. Being the smallest α-dicarbonyl compound, glyoxal establishes two hydration

equilibria in the aqueous phase, enhancing its Henry’s law constant from 1.9 M atm-1 to 3.6 × 105

M atm-1 (Ip et al. 2009), making it partition readily into atmospheric aqueous phases (Kroll et al.

2005, Liggio et al. 2005, Volkamer et al. 2007).

Assuming Henry’s law equilibrium, one can calculate the fraction of a compound residing in the

aqueous phase (faq) in a given volume of air (Eqn. 1.1):

7

𝑓𝑎𝑞 = 𝑅𝑎𝑞/𝑔𝑎𝑠

1+ 𝑅𝑎𝑞/𝑔𝑎𝑠 (1.1)

where Raq/gas is the dimensionless ratio of the equilibrium concentration of a compound in the

aqueous and the gas phases, respectively, and is calculated by Eqn. 1.2 (Seinfeld and Pandis 2006):

𝑅𝑎𝑞/𝑔𝑎𝑠 = 10−6𝐻𝑒𝑓𝑓𝑅𝑇𝐿 (1.2)

where 10-6 is a conversion factor, R is the gas constant (0.082 atm L mol-1 K-1), T is the temperature

(K), and L is the LWC (g m-3). Compounds with larger faq will more likely participate in aqueous-

phase chemistry. The calculated faq as a function of Heff for three LWC values (1 g m-3, 0.1 g m-3,

and 10 µg m-3) are shown in Figure 1.2. These three LWC values are chosen to represent typical

cloud, fog and ALW, respectively (Volkamer et al. 2009, Daumit et al. 2014). A large gap exists

between the LWC of cloud/fog and ALW due to the enormous increase of LWC during particle

activation (see Section 1.3.1). Also shown in Figure 1.2 are selected compounds with their reported

Heff values. Glyoxal and methylglyoxal are widely accepted as important aqueous-phase SOA

precursors, with a significant fraction residing in the aqueous-phase when cloud or fog is present.

Oxalic acid is a major OH oxidation product of glyoxal and methylglyoxal (Carlton et al. 2007,

Tan et al. 2009), residing nearly entirely in cloud and fog, and partially in ALW. SOA precursors

that are important in the gas-particle partitioning theory, such as α-pinene and toluene, reside

nearly entirely in the gas phase and do not participate in aqueous-phase chemistry. O3 and nitrogen

dioxide (NO2) play critical roles in gas-phase photochemistry, but are less important in the aqueous

phase due to their small Heff.

The Heff values of organic compounds can be affected by a number of factors. Lower temperature

generally enhances Heff values of oxygenated compounds, but reduces those of volatile

compounds, such as α-pinene and n-alkanes (Wania et al. 2014). Dissolved inorganic species can

affect the solubility of organic compounds, resulting in both the salting-out (reduction of Heff) and

salting-in (enhancement of Heff) effects. Salting-out effect is relevant to a wide spectrum of water

soluble organic compounds, with different salts exhibiting different magnitude of effects (Wang

et al. 2014). A significant salting-in effect was observed for glyoxal with sulfate (Ip et al. 2009).

While the mechanism of the salting-in effect is commonly considered to be due to reactions

between glyoxal and inorganic salts, Yu et al. (2011) have observed that inorganic salts affect the

8

hydration equilibria of glyoxal. For acidic organic compounds (e.g. carboxylic acids and phenols),

Heff values are significantly affected by the solution pH, as the dissociated ions are much more

soluble than the non-dissociated forms. The Heff of oxalic acid shown in Figure 1.2 is at pH 4.

Besides dissolution, organic compounds can be introduced to atmospheric aqueous phases via

nucleation scavenging (Herckes et al. 2013). When a particle activates into a cloud or fog droplet,

existing organic compounds in the original particle can dissolve into the aqueous phase. The

fraction of a compound X scavenged by nucleation scavenging can be described by its scavenging

efficiency (η) (Herckes et al. 2013):

𝜂 = 1 − 𝑋𝑖𝑛𝑡𝑒𝑟

𝑋𝑝𝑟𝑒 (1.3)

where Xinter and Xpre are the concentrations of X in interstitial aerosol and in aerosol prior to the

cloud or fog event, respectively. The η values of organic compounds have been shown to correlate

with their water solubility (Facchini et al. 1999, Collett et al. 2008), as well as the hygroscopicity

of the particles with which they are associated (Gilardoni et al. 2014). Collet et al. (2008) have

determined an average η value of 0.90 for organic compounds scavenged by radiation fog in

California. More water soluble compounds exhibit higher η values, with those for long chain

alkanes ranging from 0.5 to 0.7, while those for C6 to C9 dicarboxylic acids and levoglucosan

reaching nearly unity.

9

Figure 1.2: Calculated aqueous fraction (faq) under three selected LWC as a function of effective Henry’s law

constant (Heff). The figure also shows Heff values of selected compounds at 298 K, along with their molecular

structures. References: glyoxal (Ip et al. 2009), methylglyoxal (Zhou and Mopper 1990), oxalic acid (pH 4)

(Compernolle and Muller 2014), α-pinene (Leng et al. 2013), toluene (Kim and Kim 2014), O3 (Gershenzon et al.

2001) and NO2 (Chameides 1984).

1.4 Production and Concentration of OH Radicals in Atmospheric Aqueous Phases

The hydroxyl (OH) radical is the most important oxidant in atmospheric aqueous phases and reacts

with many dissolved organic compounds at nearly diffusion limited rates (Herrmann et al. 2010).

Despite the pivotal role that OH radical plays in atmospheric aqueous phases, its sources,

concentration and sinks are still highly uncertain.

1.4.1 Gas-Phase Partitioning and in-situ Formation of OH Radical

OH radical can be introduced to atmospheric aqueous phases both from the gas phase and via in-

situ formation in the aqueous phase. The reactive uptake of gas-phase OH to an aqueous particle

can be described by its 1st-order loss rate from the gas phase (Lelieveld and Crutzen 1991):

− 𝑑[𝑂𝐻]𝑔𝑎𝑠

𝑑𝑡= (

𝑟2

3𝐷𝑔𝑎𝑠+

4𝑟

3𝜔𝛼)−1[𝑂𝐻]𝑔𝑎𝑠 (1.4)

where [OH]gas, Dgas, and ω are the gas-phase concentration (molecule cm-3), the gas-phase

diffusion coefficient (cm2 s-1), and the mean gas-phase velocity of OH radicals (cm s-1),

respectively. The term r is the radius of the particle or droplet (cm), and α is a dimensionless

accommodation coefficient. The calculated uptake rate of OH (M s-1) as a function of particle

diameter is shown in Figure 1.3, assuming [OH]gas = 4 × 106 molecule cm-3, Dgas = 0.1 cm2 s-1, T

= 298 K and three different α values at 1, 0.1 and 0.01 to represent the highly variable mass

accommodation coefficient of OH.

Also included in Figure 1.3 are the results from studies where OH production rates in a variety of

atmospheric aqueous phases were investigated. The production rate of OH radicals in cloud, fog

and rain water is commonly determined by adding an OH probe compound into the sample and

monitoring the formation of a product compound with simulated or ambient irradiation (Faust and

10

Allen 1993, Arakaki and Faust 1998, Anastasio and McGregor 2001, Zuo 2003, Albinet et al.

2010). For aerosol liquid water, due to a lack of a direct monitoring method, the measurements

have been done for the water extract of collected particles (Anastasio and Jordan 2004, Arakaki et

al. 2006, Anastasio and Newberg 2007, Zhou et al. 2008, Nomi et al. 2012). The in-situ production

rate of OH in atmospheric aqueous phases represents one of the largest uncertainties in modeling

radical chemistry in these reaction media (Ervens et al. 2014).

As the particle size increases, the uptake rate from the gas phase decreases rapidly due to an

increasing particle volume and the limitations incurred by gas-phase diffusion. The in-situ

formation rate of OH radical also tends to be smaller in larger droplets due to dilution of OH

precursors. The conditions employed in the studies shown in Figure 1.3 are highly variable, as

summarized in Table 1.1. Experimental photon fluxes in these studies have been normalized to

ambient fluxes at different locations and time, therefore inter-comparison of the reported OH

production rates is not straightforward. However, the results all point towards a conclusion that in-

situ formation of OH radicals can be comparable and at times the dominant, source of OH radical

in atmospheric aqueous phases.

Figure 1.3: Calculated gas-particle partitioning rates and measured in-situ formation rates of OH radicals as a function

of particle diameter. The calculated rates are based on three (1, 0.1 and 0.01) values of the mass accommodation

coefficient (α), and the measured in-situ formation rates are compiled based on a number of studies, the conditions of

which are summarized in Table 1.1.

11

Table 1.1: Conditions used in the assessment of the in-situ production rate of OH radicals

Literature

Sample

Type

Particle

size1

Light

Source

OH

probe2

Normalization to ambient

photon flux

Faust and Allen, 1993 Cloud/Fog B 313 nm B Equinox, midday

Arakaki and Faust, 1998 Cloud B 313 nm B Equinox, Zenith angle=36˚

Anastasio and McGregor, 2001 Fog M 313 nm BA Winter solstice, midday at

Davis CA

Zuo, 2003 Fog A 313 nm HMSA Autumn solar noon

Anastasio and Newberg, 2007 Sea salt M Xe lamp BA Summer solstice

Zhou et al., 2008 Laboratory

Sea Salt A sunlight BA

Summer solstice, tropical

midday

Albinet et al., 2009 Rain B 365 nm B Summer midday at 45 ˚N

1M: Measured and specified in the original literature; A: Based on assumptions made in the original literature; B: Assumed from typical size

ranges of corresponding atmospheric aqueous phases (5 – 50 µm for cloud and fog, > 50 µm for rain).

2B:benzene; BA: benzoic acid; HMSA: hydroxymethanesulfonate

1.4.2 Mechanisms of in-situ Formation of OH Radical

A variety of chemical reactions can lead to in-situ formation of OH radicals in the aqueous phase.

O3 can partition from the gas phase and react with HO2 or its dissociated form, O2- (pKa of HO2 is

4.9) to form OH in cloudwater (Jacob 1986, McElroy 1986). However, this reaction has been

shown to be highly pH dependent, as O3 reacts mostly with O2- (Sehested et al. 1984). This

chemistry may be important in cloudwater, where LWC is high and acidity is low, but may be of

less importance in ALW. Direct photolysis of inorganic chromophores (i.e. NO3-, NO2

- and H2O2)

can be an important OH source in atmospheric aqueous phases. OH radical production from these

chromophores has been investigated in detail (Zellner et al. 1990, Goldstein et al. 2007, Herrmann

et al. 2010). Iron-catalyzed OH generation via Fenton and photo-Fenton reactions is particularly

important. Arakaki and Faust (1998) have observed that Fenton chemistry is the most important

in-situ formation mechanism based on measurements using authentic cloudwater samples. Ervens

et al. (2014) have also shown in their model that Fenton chemistry is likely the most important

mechanism in both cloudwater and ALW.

A less well understood OH source is from dissolved organic compounds. Dissolved organic carbon

(DOC) has been previously shown to be a major OH source in seawater (Mopper and Zhou 1990).

12

Emerging evidence also suggests the importance of this OH source in atmospheric aqueous phases.

Anastasio and Newberg (2007) have shown that the contribution of NO3- as an OH source

decreases in smaller sea salt aerosol, indicating an increasing contribution from organic

chromophores. Arakaki et al. (2006) have observed an unknown OH source exhibiting positive

correlations with the concentration of DOC. The identity of the organic chromophores and the

mechanisms of OH generation are currently unclear. Organic hydroperoxides can be an important

class of OH source candidates, given that they can be highly abundant in ALW (Docherty et al.

2005, Arellanes et al. 2006, Wang et al. 2011). However, due to their unstable nature, there is a

lack of an online detection method for organic peroxides in the aqueous phase, which significantly

hinders our understanding of their abundance and chemistry.

1.4.3 Diffuso-reactive Length (dL) of OH Radical

Due to its significant reactivity, OH radicals introduced to a particle via gas-phase partitioning

may not diffuse through the entire particle. A common approach to assess the diffusion of OH

radical is to obtain the diffuso-reactive length (dL) which describes the distance an OH radical

typically travels before reacting away and is calculated using Eqn. 1.5 (Hanson et al. 1994):

𝑑𝐿 = √𝐷𝑎𝑞

𝑘𝐼 = √𝐷𝑎𝑞

𝑘𝐷𝑂𝐶𝐼𝐼 [𝐷𝑂𝐶]

(1.5)

While the OH radical can react with inorganic species such as nitrate, SO2, H2O2 and halogen

species, the dominant sink of the OH radical is DOC (Arakaki and Faust 1998, Anastasio and

McGregor 2001, Anastasio and Newberg 2007). The 1st-order loss rate coefficient (kI) of OH

radical can be approximated by the product of the concentration of dissolved organic carbon

([DOC]) and an averaged 2nd-order rate constant [kIIDOC] of OH reacting with DOC. As the

majority of DOC in atmospheric aqueous phases remains unspeciated (Herckes et al. 2013),

Arakaki et al. (2013) have proposed an averaged, carbon-based kIIDOC value of 3.8 × 108 mol-C L-

1 s-1. The dL over a wide range of [DOC] is calculated and shown in Figure 1.4, using a Daq value

of 1 × 10-5 cm2 s-1 (Seinfeld and Pandis 2006), and the kIIDOC proposed by Arakaki et al. (2013).

Also shown in Figure 1.4 are the ranges of DOC concentration relevant to different types of

atmospheric aqueous phases. The values for marine clouds, orographic clouds and polluted fogs

are adopted from Herckes et al. (2013) which summarizes measured DOC concentrations across

13

the globe. There is no direct measurement for [DOC] in aerosol liquid water, but it has been

assumed to be at the molar level (Volkamer et al. 2009, Ervens and Volkamer 2010, Ervens et al.

2014).

The calculated values of dL are orders of magnitude smaller than the radius of the corresponding

hydrometeors, implying that OH radical introduced from the gas phase may reach only a small

portion of a particle or droplet. Recent studies also revealed enhanced viscosity of organic aerosol

(Virtanen et al. 2010, Zhou et al. 2012, Slade and Knopf 2014) as well as liquid-liquid separation

(You et al. 2012) at low RH conditions. When the diffusion of OH radicals is further hindered by

these conditions, in-situ formation of OH is expected to gain importance in aqueous-phase

processing of organic compounds relative to the gas phase.

Figure 1.4: The diffuso-reactive length (dL) of OH as a function of dissolved organic carbon (DOC) concentrations.

The loss rate of OH radicals is based on the averaged, carbon based kIIDOC value (Arakaki et al. 2013). The horizontal

bars represent the approximate DOC ranges in a variety of atmospheric aqueous phases.

14

Figure 1.5: Structures and OH rate constants (kIIOH, 298K) of organic compounds relevant to atmospheric

aqueous phases (Buxton et al. 1988, Herrmann 2003, Tan et al. 2009, Herrmann et al. 2010, Tan et al.

2012).

15

1.4.4 Steady State Concentrations of OH Radical

The steady state concentration of OH radical in aqueous aerosol, [OH]ss, can be estimated from

the ratio of its production rate (POH) and its 1st-order loss coefficient (kI):

[𝑂𝐻]𝑠𝑠 = 𝑃𝑂𝐻

𝑘𝐼⁄ (1.6)

Arakaki et al. (2013) have summarized the steady state concentration of OH radicals in different

types of atmospheric aqueous phases. Although the sources and sinks span orders of magnitude

difference among different atmospheric aqueous phases, the steady state concentration of OH

radical remains within a relatively narrow range: 0.5 to 7 × 10-15 M. However, discrepancies exist

between this measurement-based approach and other modeling-based approaches (Herrmann et al.

2010), where OH concentrations tend to be higher and to vary by orders of magnitude among

different atmospheric aqueous phases. More data and improved techniques are required to better

constrain this important parameter.

1.5 OH Reactivity and Reaction Mechanisms

1.5.1 Initiation of the Radical Chain

Aqueous-phase OH oxidation of organic compounds has been investigated widely (Buxton et al.

1988). Figure 1.5 compiles the structures and OH reactivity (kIIOH) of compounds relevant to

atmospheric aqueous-phase processing. Similar to gas-phase chemistry, the OH radical reacts with

aromatic and unsaturated aliphatic compounds essentially at the diffusion limit through radical

addition reactions (Figure 1.6, (a) and (b)).

In the absence of radical addition, OH radicals undergo rapid H-abstraction (Figure 1.6, (c)).

Organic compounds relevant to the atmospheric aqueous phases usually contain highly oxygenated

functional groups and react rapidly with OH radicals. As oxygenation proceeds further, the

reactivity drops significantly due to lack of easily abstractable hydrogens (e.g. oxalic acid and

pyruvic acid). Since dissolved molecular oxygen is abundant, reactions (a) to (c) in Figure 1.6 also

display the subsequent addition of O2 after the initiation step.

As the general rules of OH reactivity in the gas-phase chemistry are also applicable to the aqueous

phase, there is an ongoing effort to establish structure activity relationships (SAR) relevant to

16

atmospheric aqueous phases (Monod et al. 2005, Monod and Doussin 2008, Wang et al. 2009,

Doussin and Monod 2013), inspired by the gas-phase SAR (Kwok and Atkinson 1995). With the

current expansion of the aqueous-phase database, such SAR are expected to gain accuracy and

applicability.

Figure 1.6: General OH radical reactions.

17

1.5.2 Propagation of Radical Chain

Due to low Henry’s law constants, NOx does not play as pronounced a role in the aqueous phase

(Figure 1.2) as it does in the gas phase (Figure 1.6 (d)). Therefore, the radical propagation

resembles the low-NOx regime in the gas phase. In other words, the fate of peroxy radicals (RO2)

is dominated by reactions with another RO2 or with a hydroperoxy radical (HO2), rather than with

NO. Peroxy radical chemistry in the aqueous phase is highly complex and has been reviewed in

detail (von Sonntag et al. 1997). The RO2 + RO2 reaction can propagate the radical chain via

reactions (e) and (f) in Figure 1.6.

1.5.3 Termination of Radical Chain

The RO2 + RO2 reactions can also terminate the radical chain via the Russell mechanism (Figure

1.6 (g)), giving rise to a carbonyl and an alcohol. Another RO2 or an HO2 radical can also react

with RO2 to form organic peroxides (ROOR) and organic hydroperoxides (ROOH), respectively

(Figure 1.6 (h), (i)). In a modeling study, Ervens and Volkamer (2010) demonstrated that aerosol

liquid water favors formation of ROOR than ROOH. However, their results are significantly

dependent on the unimolecular decomposition rate of RO2 radicals, which represents an area that

is poorly constrained by experiments.

1.6 OH Radical Reactions Unique to the Aqueous Phase

1.6.1 Efficient Conversion of Aldehydes to Carboxylic Acids

Unique radical chemistry takes place in the aqueous phase, giving rise to products that are not

produced in the gas-phase and hence not considered in the traditional gas-particle partitioning

theory. One is the rapid conversion of aldehydes to carboxylic acids, facilitated by hydration of

the aldehyde functional group. Earlier studies have established that formic acid arises from OH

oxidation of formaldehyde in the aqueous phase, contributing to cloudwater acidity (Chameides

1984, Seinfeld and Pandis 2006). Formation of a wider variety of carboxylic acids has drawn

attention in recent years due to their contribution to SOA formation.

A series of reactions leading to carboxylic acid formation is shown in Figure 1.7. Aldehydes exist

in equilibrium with their geminal diols in the aqueous phase (Figure 1.7 (A) and (B)). OH radical

can abstract a hydrogen atom from both the aldehydic and geminal diol forms, forming their

respective alkyl radicals (Figure 1.7 (C) and (D)). These two types of alkyl radicals are also in a

18

hydration equilibrium, as shown in the case of acetyl radical (Schuchmann and von Sonntag 1988).

In the next step, oxygen molecules add to the alkyl radicals to form two types of peroxy radicals.

The peroxy radical of the geminal diol (Figure 1.7 (F)) dissociates rapidly to form a carboxylic

acid (Figure 1.7 (G)). The acylperoxy radical (Figure 1.7 (E)) can participate in other types of

chemistry (i.e. with RO2 or HO2), but can also be hydrated to form a carboxylic acid (Villalta et

al. 1996).

Numerous laboratory studies have observed rapid and significant organic acid formation from

glyoxal (Carlton et al. 2007, Tan et al. 2009, Lim et al. 2010), methylglyoxal (Altieri et al. 2008,

Tan et al. 2012), and glycolaldehyde (Perri et al. 2009, Ortiz-Montalvo et al. 2012). This formation

pathway for carboxylic acid is absent in the gas phase where formation of geminal diols is much

less likely. For this reason, organic acids, in particular oxalic acid, have been considered as tracers

for cloudwater processing in field measurements (Sorooshian et al. 2007a, 2007b). In attempts to

model aqueous phase SOA formation, organic acids are commonly used to trace the yield and mass

of aqueous SOA (Lim et al. 2010, McNeill et al. 2012, Lim et al. 2013).

Figure 1.7: Mechanisms of rapid carboxylic acid formation in the aqueous phase.

19

1.6.2 Rapid OH Oxidation of Carboxylate

OH oxidation of carboxylate species is more rapid than oxidation of the non-dissociated carboxylic

acid, resulting in a pH dependence in the reactivity of organic acids. Figure 1.8 compiles the

reactivity of a suite of carboxylic acids with their corresponding carboxylates, and this trend is

observed for all the species. More rapid OH oxidation of carboxylate is due to a charge transfer

reaction (Figure 1.9) in addition to H-abstraction (Ervens et al. 2003, Seinfeld and Pandis 2006).

The charge transfer reaction explains why oxalate dianion, a compound without any hydrogen

atoms, can also react with the OH radical. An interesting trend for diacids is that the monoanions

tend to be the most reactive towards OH radical.

Sorooshian et al. (2007a) have observed higher cloudwater oxalic acid concentrations in larger and

less acidic cloud droplets. The authors proposed that glyoxylic acid, the precursor of oxalic acid,

has dissociated in the less acidic droplets and reacted more efficiently. This study implies that

cloudwater acidity may alter the lifetime of organic acids.

Figure 1.8: OH reactivity (kIIOH) of carboxylic acids and corresponding carboxylates. Acronym: formic acid (FA),

glyoxylic acid (GA), pyruvic acid (PA), lactic acid (LA), malic acid (MA), oxalic acid (OA). References: FA, GA and

OA (Tan et al. 2009), PA (Schaefer et al. 2012), LA and MA (Herrmann et al. 2010).

20

Figure 1.9: Charge transfer reaction of carboxylate.

1.6.3 Radical Induced Oligomerization

Oligomeric compounds have been observed in laboratory OH oxidation experiments, which may

represent a formation pathway of HULIS observed in the ambient atmosphere. A radical-radical

recombination mechanism has been postulated by Turpin and coworkers (Lim et al. 2010, Tan et

al. 2012, Lim et al. 2013), where two carbon-centered radicals form a new covalent bond and give

rise to an oligomeric product (Figure 1.10 (a)). In OH oxidation of glyoxal and methylglyoxal,

radical-radical recombination gave rise to products with larger carbon numbers than the reactants.

The radical-induced nature of these reactions has been confirmed by testing the role of dissolved

molecular oxygen (Renard et al. 2013). Oxygen suppresses oligomerization by forming RO2

radicals with carbon-centered radicals. Renard et al. (2013) observed an enhancement of

oligomerization in the OH oxidation of methylvinylketone (MVK) as soon as dissolved oxygen

was depleted in their reaction system, confirming the radical nature of the oligomerization.

As the atmospheric aqueous phases are saturated with oxygen, oligomerization becomes important

only when the concentrations of the carbon-centered radicals, hence the concentrations of the

precursor organic compounds, are high enough to compete with dissolved oxygen. Lim et al.

(2010, 2013) have shown that radical-radical recombination gains importance in aqueous particles,

i.e. when glyoxal and methylglyoxal concentrations are at millimolar levels or higher. This

conclusion has later been experimentally confirmed by (Renard et al. 2013, 2014, 2015), where

they found oligomers as the dominant products of MVK OH oxidation when the MVK initial

concentrations were at 2 mM or higher. When the reactant contains unsaturated aliphatic

structures, radical addition to C=C double bonds can proceed, propagating the radical chain and

giving rise to oligomers (Figure 1.10 (b)). Renard et al (2013, 2014) proposed this mechanism in

the OH oxidation of MVK, while Kameel et al. (2013) also proposed similar mechanisms in OH

oxidation of isoprene.

21

Figure 1.10: Radical induced oligomerization mechanism, with one example each for radical-radical recombination

(a) (Guzman et al. 2006, Lim et al. 2010) and radical propagation on double bonds (b) (Renard et al. 2013).

Radical induced oligomerization has also been observed from aromatic compounds.

Oligomerization mechanisms are initiated by both carbon-centered and phenolic radicals (Sun et

al. 2010, Smith et al. 2014, Yu et al. 2014). Oligomers from aromatic compounds contain extensive

electron conjugations and are accompanied by significant light absorptivity (Chang and Thompson

2010, Yu et al. 2014), which may be partly responsible for the light absorption observed for HULIS

(Graber and Rudich 2006).

1.6.4 Radical Induced Organosulfate Formation

Radical chemistry can be responsible for organosulfate compounds observed in laboratory

experiments and ambient particle samples. A number of laboratory studies (Galloway et al. 2009,

Perri et al. 2010) observed organosulfate formation only under irradiated conditions, indicating the

importance of radical chemistry.

Perri et al (2010) have proposed a radical-radical recombination mechanism, where an alkyl radical

recombines with a sulfate radical to form organosulfates. Sulfate radical arises from H-abstraction

of sulfuric acid and bisulfate by OH radical. This mechanism is in analogy to the oligomerization

via radical-radical recombination (Figure 1.10, (a)). More recently, Schindelka et al. (2013) have

proposed a sulfate radical addition mechanism, in analogy to Figure 1.10 (b). They have also

shown that the amount of organosulfate formation scales with the number of laser pulses from

which sulfate radical is generated in their experiment. In a modeling study, McNeill et al. (2012)

found that organosulfate formation is especially important in ALW, where reactant concentrations

are high, and proposed organosulfates as tracers for chemistry occurring in aqueous particles.

22

1.7 Non-radical Chemistry in the Aqueous-phase – Nucleophilic Addition Reactions

Non-radical chemistry also gives rise to processing of organic compounds in the aqueous phase.

More than a decade ago, Jang et al. (2002) proposed that acid-catalyzed nucleophilic addition

reactions of carbonyl compounds (e.g. hydration, hemiacetal formation, and aldol condensation)

represent a mechanism of particle-phase chemistry that is responsible for additional SOA growth.

Nucleophilic addition plays a central role in the aqueous phase, giving rise to processing of organic

compounds via non-radical pathways. A classic example of aqueous-phase nucleophilic addition

is the formation of hydroxyalkylsulfonate from S(IV) species and a variety of aldehydes (Olson

and Hoffmann 1989). This group of compounds act as a reservoir of S(IV) compounds in

cloudwater and eventually contribute to cloudwater acidity. In recent years, as the connection

between aqueous-phase organic chemistry and the formation of SOA becomes clearer, a wide

variety of nucleophilic addition reactions have been investigated, with important atmospheric

implications. These reactions are expected to be particularly important in aerosol liquid water

where reactant concentrations are orders of magnitude higher than in cloudwater. The process of

droplet evaporation can also accelerate nucleophilic addition reactions (De Haan et al. 2011,

Zarzana et al. 2012, Galloway et al. 2014), as the reactant concentrations are temporarily enhanced

during evaporation. Carbonyl compounds are the most important electrophiles in the atmospheric

aqueous phases, and their chemistry is discussed in this section.

1.7.1 General Reaction Mechanism of Nucleophilic Addition

Due to the large electronegativity of oxygen, the electron density on a carbonyl group (C=O) is

significantly shifted to the oxygen atom. The carbon is hence electrophilic and subject to attack by

electron rich nucleophiles (Figure 1.11 (a)). The electrophilicity of the carbonyl group depends on

the chemical nature of the adjacent functional groups (R), in terms of both steric and electronic

effects (McMurry 2004). The bulkier and more electron donating the adjacent functional groups,

the more they stabilize the carbonyl compound from nucleophilic attack. For this reason, aldehydes

(i.e. one of the R groups is a hydrogen) are much more reactive than ketones. Carboxylic acids are

less reactive with nucleophiles, stabilized by the carboxylate resonance structures, and are not

discussed in this section.

23

1.7.2 Importance of Acid-catalysis

Since the atmospheric aqueous phases are acidic, nucleophilic addition to carbonyl compounds is

acid-catalyzed. As illustrated in Figure 1.11 (b), the oxygen on the carbonyl group can be

protonated under acidic conditions. This protonated form of carbonyl is in turn in resonance with

a carbocation form, as shown in Figure 1.11 (b). The positively charged carbon is even more

electrophilic than a neutral carbonyl, hence the carbonyl is “activated” by protonation. Acid

catalysis accelerates the reaction kinetics but does not, in principle, affect the equilibrium states.

However, given the dynamic nature of organic chemistry in atmospheric aqueous phases, acid

catalysis can significantly affect the amount of products forming in reactions discussed in this

section.

While it was generally believed that acid catalysis is initiated by strong acids such as H2SO4 and

HNO3 (Jang et al. 2002), Noziere and coworkers have proposed that amino acids (Noziere et al.

2007), the ammonium ion (Noziere et al. 2009) and carbonate ion (Noziere et al. 2010) can be

important catalysts in atmospheric aqueous phases. Given that inorganic salts can be at or beyond

their saturation concentrations in aerosol liquid water (Tang et al. 1997), catalysis by inorganic

ions can be particularly important. Assuming the universality of acid-catalysis in atmospheric

aqueous phases, the carbonyl compounds demonstrated in Figure 1.11 are in their protonated

forms.

1.7.3 Water Nucleophile and Hydration

Being the most abundant molecule in the aqueous phase, water is the most important nucleophile

in atmospheric aqueous phases. Nucleophilic addition of water to carbonyl compounds is often

referred to as the hydration reaction and gives rise to geminal diols (Figure 1.11 (c)). As hydration

reactions are reversible, all the carbonyl compounds exist, to some extent, in equilibrium with their

corresponding geminal diols. The degree of hydration directly affects the Heff value of an aldehyde,

and hence its air-aqueous partitioning (Betterton and Hoffmann 1988). The effects of highly

concentrated salts to the hydration equilibria present a poorly constrained area. Yu et al. (2011)

have shown that the hydration equilibria of glyoxal shift towards its dehydrated form in sodium

sulfate solution.

24

Figure 1.11: Nucleophilic addition reactions associated with carbonyl compounds.

25

Hydration can affect the reactivity of carbonyl compounds in several ways. First, radical induced

oxidation of geminal diols can effectively convert aldehydes into carboxylic acids, as already

demonstrated in Section 1.6.1. Second, geminal diols can act as nucleophiles themselves and add

to other carbonyls to form oligomers (See Section 1.7.4). Lastly, geminal diol formation is

accompanied by loss of the C=O double bond, hence losing light absorption induced by the n→

π* band.

1.7.4 Alcohol Nucleophile and Hemiacetal Formation

As shown in Figure 1.11 (d), hemiacetal formation proceeds via an alcohol functional group acting

as the nucleophile. For small aldehyde compounds with large hydration equilibrium constants, e.g.

glyoxal, methylglyoxal and formaldehyde, the geminal diols of these compounds act as

nucleophiles themselves, resulting in self-oligomerization (Loeffler et al. 2006, Zhao et al. 2006,

Noziere et al. 2009, Shapiro et al. 2009, Lim et al. 2010, Sareen et al. 2010, Schwier et al. 2010,

Li et al. 2011).

Sugars and anhydrosugars contain multiple alcohol functional groups and can undergo hemiacetal

formation. For example, the straight chain isomer of glucose, which contains an alcohol and an

aldehyde on the two ends of the molecule, undergoes intramolecular hemiacetal formation to form

cyclic isomers. In OH oxidation experiments of levoglucosan, (Holmes and Petrucci 2006, 2007)

have shown that the reaction intermediates of levoglucosan oligomerize via hemiacetal formation.

1.7.5 Enol Nucleophile and Aldol Condensation

Aldol condensation involves an enol nucleophile which is in equilibrium with its carbonyl form in

the aqueous phase (Figure 1.11, (e)). Nucleophilic addition of an enol to an aldehyde first leads to

an aldol intermediate, which dehydrates to form the final product. For ketones, or aldehydes that

do not preferentially form geminal diols, aldol condensation becomes the major mechanism giving

rise to oligomerization (Zhao et al. 2006, Noziere and Esteve 2007, Casale et al. 2007). A large

number of studies have observed a mixture of aldol condensation and hemiacetal formation

products from α-dicarbonyl compounds such as glyoxal and methylglyoxal (Loeffler et al. 2006,

Shapiro et al. 2009, De Haan et al. 2009, Schwier et al. 2010, Sareen et al. 2010, De Haan et al.

2011).

26

1.7.6 Similarities and Differences in Hemiacetals and Aldol Condensates

Although hemiacetal formation and aldol condensation are both proposed as important

mechanisms leading to oligomer formation in the absence of radical chemistry, fundamental

differences exist in their reaction products. The major difference is the dehydration step in aldol

condensation, leaving the aldol condensates less oxygenated compared to the hemiacetals, where

all the oxygen atoms are retained. Instead, the dehydration step leaves a double bond on the aldol

condensates. As a consequence, oligomeric aldol condensates contain extensive π-conjugation that

can absorb actinic radiation. Noziere and coworkers (Noziere and Esteve 2005, Noziere et al. 2007,

Noziere and Esteve 2007) have proposed the connection between aldol condensation products and

atmospheric Brown Carbon (See Section 1.7.8). More recently, Nguyen et al. (2013) have also

proposed highly conjugated, strongly light-absorbing oligomers arising from aldol condensation

of limonene SOA extract. The important atmospheric implication arising from the difference

between these two mechanisms is that hemiacetals are more oxygenated and less volatile, while

aldol condensation may give rise to organic chromophores absorbing the actinic radiation.

1.7.7 Hydroperoxide (ROOH) Nucleophile and Peroxyhemiacetal Formation

Organic hydroperoxides (ROOH) undergo nucleophilic addition to aldehydes to form

peroxyhemiacetals (Tobias and Ziemann 2000). This type of product has been previously proposed

to occur at particle surfaces (Tobias and Ziemann 2000, Docherty et al. 2005, Yee et al. 2012) and

is likely an important mechanism for SOA growth in a pristine (i.e. low NOx) environment

(Ziemann and Atkinson 2012). Peroxyhemiacetal formation has been shown to proceed in the

aqueous phase as well. Hydrogen peroxide (H2O2) can add to carbonyls to form the simplest form

of peroxyhemiacetal: α-hydroxyhydroperoxide (α-HHP) (Figure 1.11, (f)). Formation of α-HHP

in the aqueous phase from formaldehyde and acetaldehyde has been known since early studies

(Satterfield and Case 1954, Hellpointner and Gab 1989, Zhou and Lee 1992). However, the

potential of other carbonyl compounds forming α-HHP has not been explored.

ROOH belongs to reactive oxygen species and induces adverse health effects. Formation of

organic ROOH in atmospheric aqueous phases is of great importance in assessing the particulate

matter related health issues. It has been shown that ROOH decomposes over time in aqueous

extracts (Wang et al. 2011), thus particle extraction and offline measurements may underestimate

27

the concentration of ROOH in suspended particles. An in-situ method for the measurement of

ROOH in aqueous phase is urgently needed.

1.7.8 Nitrogen-containing Nucleophiles and Atmospheric Brown Carbon Formation

Reduced nitrogen compounds with lone-pair electrons (e.g. ammonia, primary amines and amino

acids) undergo nucleophilic addition to form imines (Figure 1.11 (g)). The reaction proceeds via

formation of a neutral carbinolamine intermediate and subsequent acid-catalyzed dehydration to

form the final product. While acid-catalysis is required, excess acid protonates the nucleophiles,

suppressing their nucleophilicity (Bones et al. 2010, Lee et al. 2013). Therefore, this reaction is

expected to be optimized in a narrow pH window.

The most crucial atmospheric implication of this reaction is formation of a class of light absorbing

organic compounds commonly referred to as atmospheric Brown Carbon (BrC) (Andreae and

Gelencser 2006). BrC species absorbs actinic radiation in the near-UV and visible range, and may

affect the direct radiative effects of organic aerosol (Feng et al. 2013). The identity and formation

mechanism of BrC are currently unclear. Imines undergo subsequent reactions in the aqueous

phase to form nitrogen-containing organic chromophores, representing a secondary source of BrC

in the aqueous phase (Shapiro et al. 2009, Sareen et al. 2010, Powelson et al. 2013). Laboratory

experiments have observed that glyoxal can undergo serial addition reactions to form imidazole

and its derivatives (Galloway et al. 2009, Yu et al. 2011, Kampf et al. 2012), and the equivalent

products have also been observed from methylglyoxal (De Haan et al. 2011, Drozd and McNeill

2014).

Nizkorodov and coworkers have observed BrC formation from the water soluble fraction of

chamber-generated SOA. They found that limonene ozonolysis SOA generated particularly

absorptive products upon aging with nitrogen containing nucleophiles (Bones et al. 2010, Nguyen

et al. 2013, Lee et al. 2014). On the contrary, SOA generated via α-pinene ozonolysis did not result

in significantly absorbing products (Updyke et al. 2012, Nguyen et al. 2013). The key difference

in SOA arising from these two isomeric precursors (i.e. α-pinene and limonene) seems to be

formation of a specific carbonyl compound, ketolimononaldehyde, as a second generation product

only in the limonene system (Nguyen et al. 2013, Laskin et al. 2014).

28

1.8 Removal of Organic Compounds in Aqueous-phase

Atmospheric aqueous phases play pivotal roles in the removal processes of organic compounds,

with wet deposition being the major removal mechanism of accumulation mode organic aerosol,

responsible for 70 to 85 % of its total sink (Kanakidou et al. 2005). Field measurements have

confirmed that fog scavenging enhances the deposition velocities of organic aerosol components

(Herckes et al. 2007, Collett et al. 2008). While these are physical removal processes, aqueous-

phase chemistry also results in chemical removal of certain organic compounds, significantly

affecting their atmospheric lifetime.

Isocyanic acid (HNCO), a toxic pollutant arising from pyrolytic processes, represents an extreme

example where its only atmospheric sink is in the aqueous phase. HNCO does not contain an

abstractable hydrogen atom and does not react with OH radical rapidly (Tsang 1992), nor does it

absorb actinic radiation to photolyze (Dixon and Kirby 1968). However, it is readily water soluble,

and undergoes an irreversible hydrolysis reaction (Roberts et al. 2011). Therefore, the gas-aqueous

partitioning of HNCO and the kinetics of its aqueous-phase chemistry play critical roles in

governing the atmospheric lifetime of this harmful compound.

Organonitrates species, with a general structure RONO2, undergo hydrolysis in the aqueous phase

and give rise to the corresponding alcohol (ROH) and HNO3 (Szmigielski et al. 2010, Darer et al.

2011, Hu et al. 2011). While the hydrolysis rates of primary and secondary organonitrate species

are small, the hydrolysis lifetimes of tertiary organonitrate species are on the order of minutes

under atmospherically relevant conditions (Darer et al. 2011). The fast hydrolysis of tertiary

organonitrates reflects the stability of the carbocation intermediate forming in its hydrolysis

mechanism (Szmigielski et al. 2010). Recent laboratory investigations for isoprene-derived

organonitrates have observed tertiary structural isomers (Teng et al. 2014, Lee et al. 2014). As

organonitrate species are temporary reservoirs of NOx, aqueous-phase removal of these species

essentially leads to removal of reactive nitrogen species from the atmosphere.

Aqueous-phase OH oxidation can remove organic compounds very efficiently. For example,

laboratory studies have found that the aqueous-phase oxidation lifetime of levoglucosan is on the

order of hours (Hoffmann et al. 2010, Teraji and Arakaki 2010). Levoglucosan is a widely

employed molecular tracer for biomass burning (Simoneit 2002), which is typically assumed to be

chemically inert in chemical mass balance receptor models (Robinson et al. 2006). Under humid

29

and sunlit conditions, where photochemistry in the aqueous-phase is active, such rapid removal of

levoglucosan in the aqueous phase may significantly affect the accuracy of biomass burning source

apportionment.

Aqueous-phase chemistry affects the optical properties of organic chromophores. Recent

laboratory studies have observed somewhat contradictory results on the effect of aqueous-phase

processing to the light absorptivity of BrC species. Aqueous-phase OH oxidation of phenolic

compounds has been observed to enhance the solution light absorptivity (Gelencser et al. 2003,

Chang and Thompson 2010), while other studies have observed rapid decay of color (photo-

bleaching) of BrC upon aqueous-phase photolysis (Bateman et al. 2011, Sareen et al. 2013, Lee et

al. 2014). The results imply that aqueous-phase processing can be a significant removal process

for BrC. The effect of OH oxidation on the absorptivity of BrC is yet to be explored.

1.9 Sampling and Measurement Techniques for Aqueous-phase Organic Compounds

1.9.1 Sampling Techniques for Cloud and Fog Water

Bulk cloud and fog water samples have been commonly collected using the Caltech active strand

cloudwater collector (CASCC) (Demoz et al. 1996). A fan placed at the inlet draws the ambient

air into the collector and accelerates the air against vertical cylindrical Teflon strands. While small

particles (i.e. gas molecule and aerosol) follow the air stream and pass by the strands, large

particles (i.e. cloud and fog droplets) collide with the strands due to inertia, with their liquid content

collected at the base of the strands. The original CASCC was designed to have a droplet cut-size

at 3.5 µm, but later modifications also enabled size resolved collection. The strength of CASCC is

that it collects a large volume of sample that can be analyzed using offline analytical techniques.

While CASCC can collect only bulk samples, continuous sampling techniques for cloud and fog

water have also been developed, and the counterflow virtual impactor (CVI) represents one of such

techniques. The type generated by Noone and coworkers (Noone et al. 1988b) has been employed

in both ground-based and aircraft measurements. The ambient inlet flow meets a counterflow

(clean and warm air) inside the CVI, generating a virtual stagnant plane, whereby only large

droplets with sufficient inertia can pass and be sampled. Once the sampled droplets are exposed to

30

the dry and warm counterflow, the droplets evaporate and give rise to droplet residues. The CVI

has been employed to investigate size distribution and inorganic salt contents in these droplet

residues (Noone et al. 1988a, Noone et al. 1992). To better exploit the continuous nature of CVI,

it has been coupled to online aerosol mass spectrometry in a few previous studies for online

chemical characterization of the droplet residues (Hayden et al. 2008, Lee et al. 2012).

1.9.2 Recent Development of Extraction and Measurement of Water Soluble Organic Carbon Associated with Particles

Due to small LWC, there is currently no method for direct sampling and measurement of the

organic composition of ALW. The water-extractable fraction of particulate matter, also referred to

as water soluble organic carbon (WSOC), is commonly used to imply the chemical composition

in the original particle and ALW.

Filter collection and extraction is the most widely employed method to obtain the WSOC fraction.

While the extraction has been conducted by either shaking or sonicating the filter in bulk aqueous

phase, Laskin and coworkers have developed nanospray desorption electrospray mass

spectrometry (nano-DESI) where extraction can be conducted on the filter surface (Roach et al.

2010). Briefly, an aqueous reservoir (the solvent bridge) is created on the filter surface to extract

analytes. The solvent bridge is connected to two nano capillaries, with the first capillary

continuously supplying the solvent to the bridge, and the second capillary carrying the solvent and

extracted analytes to an electrospray ionization mass spectrometer (ESI-MS). Being able to

conduct extraction directly on the filter, nano-DESI avoids artifacts arising from extensive

extraction procedures.

Collection of a filter sample typically takes hours. To improve time resolution of particle

collection, a continuous extraction method, particle-into-liquid sampler (PILS) has been developed

(Orsini et al. 2003). Aerosol sampled by a PILS is exposed to a supersaturated condition, where

the particles grow into large droplets, following the activation process described in Section 1.3.1.

The activated droplets are collected into the aqueous phase using inertial impaction. PILS can be

coupled to any analytical methods that can make continuous aqueous-phase measurements

(Section 1.9.3). Weber and coworkers have coupled PILS to a variety of analytical methods to

make semi-continuous measurements of different aspects of ambient aerosol. Orsini et al. (2013)

have used ion chromatography downstream of a PILS to measure organic acids associated with

31

ambient aerosol. Miyazaki et al. (2009) have coupled a semi-continuous total organic carbon

analyzer to quantify the total WSOC, while Zhang et al. (2013) further coupled a liquid waveguide

capillary cell, a sensitive UV-Vis spectrometer, to quantify the amount of BrC in WSOC.

1.9.3 Application of Online Mass Spectrometry to Aqueous-Phase Detection.

Online mass spectrometry (MS) exhibits excellent detection sensitivity and high time resolution,

representing the ideal analytical method for a rapidly evolving chemical composition in the

aqueous phase. Turpin and coworkers have employed an online ESI-MS to monitor aqueous-phase

OH oxidation of a variety of organic compounds, including glycolaldehyde (Perri et al. 2009),

glyoxal (Tan et al. 2009), methylglyoxal, (Tan et al. 2010) and acetic acid (Tan et al. 2012).

Aerosol mass spectrometer (AMS) has made a tremendous contribution in monitoring the organic

composition of submicron aerosol (Jayne et al. 2000, Canagaratna et al. 2007). Lee et al. (2011)

have developed a novel method to apply this powerful instrument to aqueous-phase detection. By

atomizing the aqueous solution and drying the generated droplets, the bulk aqueous-phase is

converted into particles, a detectable form for AMS. This method has been first applied in

characterizing the chemical composition of authentic cloudwater and WSOC (Lee et al. 2011, Lee

et al. 2012), and later adopted by a number of laboratory investigations of aqueous chemistry

(Aljawhary et al. 2013, Daumit et al. 2014, Yu et al. 2014).

The past decade has also seen a rapid development of gas-phase MS techniques, represented by

proton transfer reaction mass spectrometry (PTR-MS) and chemical ionization mass spectrometry

(CIMS). These techniques employ soft ionization methods and are suited for obtaining molecular-

level information for kinetic and mechanistic studies. Sampling techniques have been developed

to apply these gas-phase MS techniques to the measurement of condensed-phase organics, by

thermally desorbing the organic compounds to the gas-phase. Holzinger et al. (2010) have

developed a thermal-desorption PTR-MS (TD-PTR-MS), while Yatavelli and Thornton (2010)

have introduced a micro-orifice volatilization impactor (MOVI) coupled to a CIMS instrument.

The similarity between the two methods is that aerosol samples are first collected and concentrated

on an impactor, followed by programmed thermal-desorption. As the sampling is divided into a

collection phase and a thermal-desorption phase, these setups can separate condensed-phase

organic compounds from the gas-phase compounds and make semi-continuous measurements.

32

Continuous measurement of condensed-phase organic compounds has been enabled by the

development of aerosol chemical ionization mass spectrometry (Aerosol CIMS) (Hearn and Smith

2004). In this technique, aerosol sample is continuously introduced through a heated volatilization

line where thermal-desorption occurs. Aerosol CIMS has been applied in laboratory generated

particle samples (Hearn and Smith 2006, McNeill et al. 2008). The first application of Aerosol

CIMS to aqueous-phase chemistry was by Sareen et al. (2010), where they atomized aqueous

mixtures of methylglyoxal and ammonium sulfate and analyzed their chemical composition using

an iodide water cluster CIMS. Given the continuous nature of this technique, it is expected to be

highly valuable in monitoring rapidly evolving chemical systems, such as OH oxidation in the

aqueous phase.

1.10 Summary and Objectives

Studies from the last decade have indicated atmospheric aqueous phases as important reaction

media, where organic compounds undergo chemical reactions, i.e. aqueous-phase processing.

Aqueous-processing is accompanied by decay of the precursor compounds and formation of non-

volatile products. Therefore, aqueous-phase organic chemistry gives rise to organic compounds

that can contribute to SOA formation, in addition to compounds condensing from the gas phase.

As our knowledge of atmospheric aqueous-phase chemistry is incomplete, a better understanding

of the relevant kinetics and mechanisms will contribute to a better assessment of the effects of

atmospheric aerosol to air quality and climate change. Development of online detection methods

for aqueous-phase organic compounds in both the laboratory and the field is urgently needed.

Particularly, application of soft ionization mass spectrometry will be important and timely for the

detection of unstable compounds and to provide molecular-level information.

The goals of this work is to further our understanding of the reactions of organic compounds in

the aqueous phase, as well as the partitioning of organic compounds to the aqueous-phase. The

priority is given to providing quantitative information for the improvement of cloudwater

chemistry models. Specific objectives involve:

Development of an online measurement technique, where online CIMS is applied to

monitor aqueous-phase organic chemistry.

33

Investigation of aqueous-phase OH oxidation of SOA precursors: glyoxal and

methylglyoxal.

Kinetic and mechanistic investigation of aqueous-phase OH oxidation of levoglucosan.

Quantification of α-HHPs forming in the aqueous phase and its impact on the partitioning

of aldehydes to atmospheric aqueous phases.

Investigation of the effects of photochemical processing on the optical properties of BrC

species.

Measurement of cloud partitioning of HNCO using online CIMS coupled to a CVI.

In Chapter 2 and 3, a new Aerosol CIMS system is utilized for laboratory investigation of OH

oxidation of glyoxal, methylglyoxal and levoglucosan. Comprehensive product analyses for these

precursors are conducted. Particularly in Chapter 3, a high mass resolution CIMS is employed, and

novel analysis frameworks are introduced to offer insights to detailed reaction mechanisms.

In Chapter 4, formation of α-HHPs was quantified using a combination of online PTR-MS and

offline nuclear magnetic resonance (NMR) spectrometry. Such organic hydroperoxides forming

in the aqueous-phase represent a class of unrecognized compounds with significant environmental

implications.

In Chapter 5, the effects of photochemistry on the absorptivity of BrC species were investigated,

focusing on the imine-mediated species (Section 1.7.8) and nitrophenols as surrogates for biomass

burning BrC.

Finally, in Chapter 6, an online CIMS was for the first time coupled to a CVI for in-situ

measurement of organic compounds dissolved in ambient cloudwater, with focus on the cloud

partitioning of HNCO.

34

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Chapter 2

Investigation of Aqueous-Phase Photooxidation of Glyoxal and

Methylglyoxal by Aerosol Chemical Ionization Mass Spectrometry:

Observation of α-hydroxyhydroperoxide Formation

Reproduced with permission from Journal of Physical Chemistry A 116 (24), pp 6253–6263

DOI: 10.1021/jp211528d Copyright © 2012 American Chemical Society.

54

Abstract

Aqueous-phase processing of glyoxal (GLY) and methylglyoxal (MG) produces highly

oxygenated, less volatile organic acids that can contribute to SOA formation and aging. In this

study, aerosol chemical ionization mass spectrometry (Aerosol CIMS) is employed to monitor

aqueous-phase photooxidation of GLY and MG. Using iodide (I−) as the reagent ion, Aerosol

CIMS can simultaneously detect important species involved in the reactions: organic acids,

peroxides, and aldehydes, so that the reconstructed total organic carbon (TOC) concentrations

from Aerosol CIMS data agree well with offline TOC analysis. This study also reports the first

direct detection of α-hydroxyhydroperoxide (α-HHP) formation from the reaction of H2O2 with

GLY or MG. The formation of α-HHPs is observed to be reversible, and their formation

equilibrium constants are determined to be between 40 and 200 M−1. Results of this study suggest

that α-HHPs can form additional formic acid and acetic acid via photooxidation and regenerate

GLY or MG during photooxidation, compensating their loss. α-HHP formation needs to be further

studied for inclusion in aqueous-phase chemical models given that it may affect the effective

Henry’s law constants of carbonyls in the atmosphere.

2.1 Introduction

It is now evident that aqueous-phase processing can be a significant formation and aging pathway

of secondary organic aerosol (SOA) (Blando and Turpin 2000, Loeffler et al. 2006, Fu et al. 2009,

Lim et al. 2010, Ervens and Volkamer 2010, Ervens et al. 2011, Kaul et al. 2011), a major fraction

of atmospheric submicrometer particles (Zhang et al. 2007) that causes adverse health effects,

visibility degradation and affects global climate. Aqueous-phase oxidation can convert water-

soluble volatile organic compounds (VOCs) into highly oxygenated, less volatile compounds that

can contribute to SOA mass upon water evaporation. Inclusion of this SOA formation mechanism

may improve agreement between field observations and traditional models (Volkamer et al. 2006)

in which SOA formation is governed by thermodynamic partitioning of gas-phase oxidation

products alone (Odum et al. 1996). Aqueous-phase processing is also an additional chemical aging

process causing continuous modification of physicochemical properties of organic aerosol, such

as hygroscopicity (Jimenez et al. 2009, Wong et al. 2011), light absorption (Ramanathan et al.

2007), and oxidative stress to the human body. However, due to its complicated nature, many

55

aspects of aqueous-phase processing and its contribution to the SOA budget are still not fully

understood.

Glyoxal (GLY) and methylglyoxal (MG) are ubiquitous dicarbonyl VOCs in the atmosphere. They

originate from both biogenic and anthropogenic precursors, with photooxidation of isoprene being

their dominant source (Fu et al. 2008). They have been frequently employed as model compounds

in numerous laboratory and modeling studies of atmospheric aqueous-phase processing (Carlton

et al. 2007, Altieri et al. 2008, Fu et al. 2009, Tan et al. 2009, Shapiro et al. 2009, Ervens and

Volkamer 2010, Lim et al. 2010, Tan et al. 2010, Schwier et al. 2010, Sareen et al. 2010, Lee et

al. 2011, Lee et al. 2011). Specifically, GLY and MG can efficiently partition into pure water via

formation of their hydrated structures (i.e., geminal diols), resulting in high effective Henry’s law

constants of 4.19 × 105 M atm−1 for GLY (Ip et al. 2009) and 3.71 × 103 M atm−1 for MG (Betterton

and Hoffmann 1988). There is growing evidence that the presence of inorganic and organic species

in aqueous solution can further enhance their Henry’s law solubility (Ip et al. 2009, Volkamer et

al. 2009, Yu et al. 2011), in part due to various types of aqueous-phase reactions including

enhanced hydration effects (Ip et al. 2009, Yu et al. 2011), oligomerization (Zhao et al. 2006, Lim

et al. 2010), and formation of nitrogen-containing (Noziere et al. 2009, De Haan et al. 2011) and

sulfur-containing compounds (Sareen et al. 2010).

Under solar radiation, aqueous-phase GLY and MG can be rapidly photooxidized (Carlton et al.

2007, Tan et al. 2009, Tan et al. 2010), via irreversible reactions that can form SOA materials

which have larger molecular weight and/or lower volatility (Lim et al. 2010). Depending on the

conditions of gas−aqueous phase transitions, aqueous-phase photooxidation of GLY and MG can

be a loss mechanism comparable to their gas-phase photooxidation and has been studied in detail

(Lim et al. 2005, Carlton et al. 2007, Tan et al. 2009, Lim et al. 2010, Tan et al. 2010, Lee et al.

2011). The proposed reaction scheme is shown in Figure 2.1 (Lim et al. 2005, Altieri et al. 2008,

Lim et al. 2010). The major products include highly oxygenated organic acids such as oxalic acid,

glyoxylic acid, and pyruvic acid. The products from multiple oxidation generations are expected

to participate in the formation of oligomer, nitrogen- and sulfur-containing compounds.

Furthermore, volatile products such as formic acid and acetic acid can repartition into the gas

phase. Their formation via aqueous-phase processing may partially explain the current

underestimation of the global budget of gas-phase formic acid and acetic acid (Paulot et al. 2011).

56

Figure 2.1: Simplified reaction mechanisms of aqueous-phase photooxidation of GLY (Lim et al. 2010) and MG (Lim

et al. 2005, Altieri et al. 2008). The two-way arrows represent reversible processes, whereas the one-way arrows

represent irreversible OH oxidation.

The major advances described above in our understanding of the mechanism of the aqueous-phase

photooxidation of these dicarbonyls have arisen from both offline analysis (Monod et al. 2005,

Carlton et al. 2007, Altieri et al. 2008) or a combination of online and offline analytical methods,

many conducted by Turpin and co-workers (Tan et al. 2009, Tan et al. 2010, Lee et al. 2011).

These studies focused on the identification of products and the determination of their formation

kinetics, based on which aqueous-phase chemistry models have been developed. However, all

offline analysis is subject to potential secondary reactions occurring in the solution prior to analysis

(Stefan and Bolton 1999, Tan et al. 2009). In addition, detection and quantification of unstable

(e.g., α-hydroxyhydroperoxides) or highly volatile species (e.g., acetic acid and formic acid) are

especially challenging, so that the current aqueous-phase chemistry models may be incomplete.

Our previous work monitored aqueous-phase photooxidation of GLY with online aerosol mass

spectrometry (AMS), offline ion chromatography (IC), and total organic carbon (TOC)

measurement (Lee et al. 2011). It was observed that the reconstructed TOC calculated from the

AMS and IC speciated data was significantly lower than the measured TOC in the early stages of

57

photooxidation, suggesting incomplete characterization of the oxidizing solution. On the basis of

the AMS measurement, Lee et al. (2011) first proposed that this unrecognized compound was a α-

hydroxyhydroperoxide (α-HHP) resulting from the rapid reaction between GLY and H2O2. α-HHP

formation from other atmospherically relevant water-soluble aldehydes (e.g., formaldehyde and

acetaldehyde) and H2O2 is also favored (Hellpointner and Gab 1989). Because AMS is not a highly

species-specific technique when one observes a mixture of compounds, and α-HHPs are likely to

be unstable for offline analysis, it is necessary to develop an online analytical technique that allows

direct detection of α-HHPs. For the current study, we have applied a real-time mass spectrometry

measurement system with a soft ionization source, aerosol chemical ionization mass spectrometry

(Aerosol CIMS) (Hearn and Smith 2004), to provide simultaneous detection of GLY, MG, α-HHPs

and both volatile and less-volatile photooxidation products. This is a complement to earlier online

analyses conducted using electrospray ionization mass spectrometry (ESI-MS) (Carlton et al. 2007,

Tan et al. 2009, Tan et al. 2010), making use of a different sample preparation method and mass

spectrometric ionization technique. The goal of the study was to demonstrate the oxidation

mechanisms of GLY and MG using Aerosol CIMS, and to confirm the formation of α-HHPs in the

reaction systems. In particular, total organic carbon (TOC) concentration in the solution was

reconstructed using Aerosol CIMS to examine its agreement with the measured TOC

concentration, and to assess the degree of oligomer formation.

2.2 Experimental Methods

The schematic diagram of the experimental apparatus is shown in Figure 2.2, with each component

of the system explained in this section.

2.2.1 Photooxidation of Aqueous Solution.

The conditions of the photooxidation experiments conducted are listed in Table 2.1. GLY and MG

solutions were prepared in 1 L pyrex reaction bottles using 18 mΩ Milli-Q water as described by

Lee et al. (2011). Because GLY and MG may exist in dimer or trimer forms in the concentrated

GLY (Sigma-Aldrich, 40 wt % in water) and MG (Sigma-Aldrich, ∼60% in water) stock solutions,

sufficient time (∼12 h) was given for them to reach their hydration equilibria in the reaction bottle

under dark conditions prior to the experiments. For consistency, ammonium sulfate (AS; 0.2 mM)

58

was added to the solution because it was used as an internal standard for AMS measurement in our

previous study (Lee et al. 2011). Because concentrated solutions of AS only react slowly with GLY

and MG to form nitrogen- and sulfur-containing compounds (Shapiro et al. 2009, Noziere et al.

2009, Galloway et al. 2009, Sareen et al. 2010), it is assumed that a low concentration of AS, 0.2

mM, does not significantly react with organics in the solution compared to OH radical reaction

during our experimental time scale. The AS control experiment (Table 2.1), where GLY

photooxidation was performed without addition of AS, did not show major differences, confirming

that AS does not significantly affect the photooxidation kinetics.

Figure 2.2: Schematic description of Aerosol CIMS and photooxidation cell.

Photooxidation of GLY was conducted in two concentration regimes, 3 and 0.3 mM, to investigate

possible concentration effects, whereas MG photooxidation was only conducted at 3 mM. H2O2

(Sigma Aldrich, 30 wt % in water) was used as the source of OH radicals upon photolysis. The

H2O2 concentrations used in the experiment were 13 and 1.3 mM for the 3 and 0.3 mM

concentration regimes, respectively (Table 2.1). These H2O2 concentrations were expected to give

a OH radical concentration of approximately 10−14 to 10−13 M in the solution during

photooxidation, which corresponds to ambient cloudwater concentrations (Jacob 1986). After

H2O2 addition, 30−40 min was given for α-HHPs to form and reach their equilibria without

exposure to light. Some 3 mM GLY photooxidation experiments were also conducted without any

waiting period to elucidate the effect of α-HHP to the photooxidation. In these experiments, the

59

photooxidation was initiated immediately after the addition of H2O2. In all experiments,

photooxidation was initiated by a 254 nm mercury lamp (UVP, constructed to remove the 185 nm

line) immersed in the reaction solution, and the length of each experiment was approximately 4 h.

During the entire experiment, the solution was atomized by a constant output atomizer (TSI, Model

3076) using ultrapure compressed air (BOC, grade 0.1), and the generated aerosol particles were

analyzed by Aerosol CIMS.

Table 2.1: Experimental Conditions

Photooxidation Experiments GLY

(mM) MG (mM) H2O2 (mM) AS (mM) Light

3 mM glyoxal (GLY) 3 0 13 0.2 Yes

0.3 mM GLY 0.3 0 1.3 0.2 Yes

3 mM methylglyoxal (MG) 3 0 13 0.2 Yes

Control Experiments

Dark Control GLY 3 0 13 0.2 No

Dark Control MG 0 3 13 0.2 No

H2O2 Control GLY 3 0 0 0.2 Yes

H2O2 Control MG 0 3 0 0.2 Yes

Irradiation of water 0 0 0 0.2 Yes

H2O2 to water 0 0 13 0.2 No

A series of control experiments was also conducted (Table 2.1). A dark control was conducted to

investigate dark reactions of GLY or MG with H2O2, whereas a H2O2 control was performed to

investigate direct photoreactions of GLY and MG without addition of H2O2. The purity of the

water used was also examined by H2O2 addition and by exposure to direct and indirect photolysis

to elucidate any potential organic formation from water impurities.

2.2.2 Aerosol CIMS

The Aerosol CIMS system employs a heated inlet line to volatilize particle-phase organic

compounds, thus detecting gas- and particle-phase organics simultaneously. Aerosol CIMS was

first developed by Hearn and Smith (2004) and has been used very successfully for studies of

60

heterogeneous and aqueous-phase chemistry (McNeill et al. 2008, Sareen et al. 2010). Here, we

apply Aerosol CIMS to investigate bulk aqueous-phase photooxidation. In the current study, the

particle flow generated from the atomizer was diluted with 3.0 standard liter per minute (slpm) of

ultrapure N2 gas (BOC, grade 4.8). The diluted flow was subsequently sent into a volatilization

line made of 40 cm long silicon-coated metal tubing (SilcoNert 2000), which was heated to 105 ±

5 °C using a heating tape and monitored by a thermocouple. This temperature was chosen because

it enables the detection of α-HHPs and both monohydrated and dihydrated GLY. The sample flow

entering the CIMS was measured to be 4.5 slpm, which is controlled by a critical orifice at the

entrance to the ion molecular region (IMR), with excess flow going to the exhaust line.

The CIMS is a home-built unit using I− as the reagent ion and a quadrupole as the mass analyzer

(Escorcia et al. 2010). The reagent ion is generated by flowing 6 splm of N2 gas over a homemade

CH3I permeation tube held at 70 °C. The flow containing CH3I vapor is then sent through a Po210

radioactive cell (NRD, Model 2031) from which I− is generated. The reagent ion meets the sample

flow in the IMR of the CIMS, where organic acids, peroxides, and aldehydes are ionized by

reactions R2.1, R2.2 and R2.4 (McNeill et al. 2008, Sareen et al. 2010):

RC(O)OH + I-•H2O → I-•RC(O)OH + H2O (R2.1)

ROOH + I-•H2O → I-•ROOH + H2O (R2.2)

RCHO + H2O ↔ RC(OH)2 (R2.3)

RC(OH)2 + I-•H2O → I-•RC(OH)2 + H2O (R2.4)

Chemical ionization using I− is a soft ionization technique, causing minimal fragmentation of the

parent molecules. Organic acids are ionized mostly via ligand transfer reaction from water clusters

of I− (I−·H2O) (R2.1) and are detected at the mass to charge ratio (m/z) of the molecule plus that of

I− (m/z = 127). Hydrogen peroxide and organic peroxides are also detected by the same ligand

transfer reaction (R2.2). Aldehydes are not ionized by I− directly, but they form geminal diols via

hydration reactions in the aqueous phase (R2.3). These geminal diols are ionized via the same

ligand transfer reaction (R2.4); therefore, aldehydes can be detected at the m/z of the molecule plus

18 (from H2O) and 127 (from I−). For dialdehydes such as GLY, geminal diols at the two hydration

steps were both detected. Herein, the terms GLY·1H2O and GLY·2H2O will be used to represent

61

GLY monohydrate and dihydrate, respectively. GLY·1H2O was the dominant GLY peak detected

by Aerosol CIMS, so that GLY·1H2O was used to estimate the GLY concentration in the solutions.

Only one geminal diol (MG·1H2O) was detected for MG, and it is used to estimate MG

concentration in the solution.

The calibration of the Aerosol CIMS was conducted by atomizing standard solutions with known

concentrations of GLY, MG, and their major products using the same experimental settings

mentioned above. This method enables the direct quantification of the target compounds, at the

same time accounts for the effects of temperature, ionization efficiency, and water vapor that

control the detection sensitivity of Aerosol CIMS. The raw signal of each species was normalized

to the reagent ion (I− at m/z 127) to account for the effect of any changes in the number of reagent

ions during the experiment. At the beginning of each experiment, Milli-Q water with 0.2 mM AS

was atomized for 30−40 min to stabilize the volatilization line temperature and to obtain a

background. The background values were subtracted from analyte signals. The linearity of the

calibrations was generally excellent (R2 > 0.98), and the measurement uncertainty for most of the

organic acids was determined to be ∼5% for a single run, except for pyruvic acid whose ionization

efficiency drifted over time. We estimate its measurement uncertainty to be ∼15%. There is more

uncertainty associated with GLY and MG quantification due to the sensitivity of their hydration

equilibria to temperature and the chemical composition of the solution, making it more difficult to

estimate the overall uncertainties. These uncertainties will be discussed in the TOC results section.

The detection sensitivity of the analytes, in general, is constant during an experiment but varies to

some degree between days. For this reason, a calibration was performed prior to each

photooxidation experiment. The following species were quantified with this calibration method:

GLY, MG, formic acid (FA) (Fluka, 50% in water), glyoxylic acid (GA) (Sigma Aldrich, 50 wt %

in water), oxalic acid (OA) (Fisher Scientific, in dihydrate form), pyruvic acid (PA) (Sigma

Aldrich, 98%), glycolic acid (GCA) (Sigma Aldrich, 99%), acetic acid (AA) (Fisher Scientific,

99.7%), malonic acid (MA) (Fisher Scientific, 99%), and succinic acid (SA) (Fisher Scientific).

The detection limits of the analytes are generally below 0.02 mM, except for GLY and AA. Their

detection limits are estimated to be 0.05 mM and 0.07 mM, respectively.

62

2.2.3 Offline TOC and Complementary IC Analysis

The total organic carbon (TOC) concentration was analyzed by an offline TOC analyzer (Shimadu

TOC-VCPN) in a similar way as our previous studies (Lee et al. 2011, Gao and Abbatt 2011). The

TOC analyzer quantifies the total carbon concentration in the solution by converting all the carbon

containing species into CO2 at a high temperature using an oxidation catalyst. The CO2 generated

is detected by a nondispersive infrared detector. Meanwhile, the inorganic carbon concentration in

the sample solution is quantified by converting inorganic carbon species into CO2 using HCl,

followed by the same CO2 detection. Potassium hydrogen phthalate was used to calibrate the total

carbon measurement, whereas sodium carbonate/sodium bicarbonate were used for the calibration

of inorganic carbon. The difference between the measured total carbon and inorganic carbon is the

TOC concentration. TOC samples were collected from the experimental solution every 30 min

during the photooxidation. The samples were sealed, covered with aluminum foil, and refrigerated

at 5 °C until analysis. The measurement uncertainty of the TOC analysis is 10%.

Because the m/z of MG·1H2O overlaps with the m/z of OA, our CIMS with unit mass resolution

could not distinguish these two compounds. Offline ion chromatography (IC) was employed to

quantify OA in the MG photooxidation experiments to assist the Aerosol CIMS data analysis. The

analysis was conducted using a Dionex ICS 2000 system with AS19 anion exchange column under

suppressed conductivity detection using an ASRS 300 conductivity suppressor. The eluent was

potassium hydroxide (KOH) with a flow rate of 1 mL min−1. The eluent concentration gradient

was programmed as a previous study (VandenBoer et al. 2011). The measurement uncertainty of

the IC analysis was estimated to be within several percent. IC samples were collected from the

photooxidation solution every hour and were analyzed on the same day of the experiment, keeping

them sealed, covered with aluminum foil and refrigerated. A polynomial curve was fitted to the

OA concentration time profile obtained from IC analysis, and this expression was used to back-

calculate the Aerosol CIMS signal responsible for OA. From there, the OA and MG·1H2O signals

were separated, and the concentration profile of MG was obtained.

63

2.3 Results and Discussions

2.3.1 Formation of α-Hydroxyhydroperoxides (α-HHPs) in Dark Control Experiments

Formation of a class of compounds was witnessed from the dark control experiment of GLY and

MG, but not from addition of H2O2 into pure water. These compounds have m/z of the geminal

diols of GLY or MG plus 127 (from I−) and 34, the m/z of a H2O2 molecule. We propose that these

compounds are α-hydroxyhydroperoxides (α-HHPs) formed via reactions between H2O2 and GLY

or MG (Figure 2.3).

Figure 2.3: Pathways showing formation of α-hydroxyhydroperoxides.

Formation of α-HHP proceeds via nucleophilic addition of H2O2 to the aldehyde functional group

(Sun et al. 2006, Mucha and Mielke 2009). α-HHP formation from reactions between H2O2 and

carbonyls has been long recognized (Hellpointner and Gab 1989, Stefan and Bolton 1999). In the

case of the current study, H2O2 reacts with GLY and GLY·1H2O (R2.5 and R2.6, Figure 2.3) to

form 2-hydroxy-2-hydroperoxyethanal (HHPE) and its hydrated counterpart (HHPE·1H2O). For

MG, H2O2 can react with either the aldehyde (R2.7) or the ketone (R2.8) functional group to form

a pair of structural isomers: hydroxyhydroperoxyacetone (HHPA) and 2-hydroxy-2-

64

hydroperoxypropanal (HHPP). Note that Aerosol CIMS was unable to separate these two structural

isomers. MG·1H2O can also react with H2O2 (R2.9) to form hydrated HHPP (HHPP·1H2O).

Formation of the four HHPs shown in Figure 2.3 has been confirmed using Aerosol CIMS by

observations of the signal increase at their corresponding m/z (Figure 2.3) in the dark control

experiments. HHPE and HHPA/HHPP were the major α-HHP peaks observed.

Figure 2.4: Formation of α-HHPs in dark control experiments. H2O2 (13 mM) was added to 3 mM of GLY (a) or 3

mM of MG (b) solutions at time (I), and quenched at time (II) by addition of catalase from bovine liver. α-HHPs

formed sharply after the addition of H2O2 and reached equilibrium values approximately 40 min after the addition.

After quenching of H2O2, α-HHPs decayed to zero and reversibly formed GLY or MG.

Figure 2.4a shows an example dark control experiment of 3 mM of GLY. Immediately after H2O2

was added to GLY solution at time (I), a significant increase of HHPE signal was detected until

equilibrium was established in 40 min. At this point, one-third of GLY has been consumed,

indicating that approximately 1 mM of total α-HHP was present in the solution. At time (II), 2

drops of catalase from bovine liver (Sigma Aldrich, 28 mg protein/mL; 21600 units/mg protein)

were added to the solution to quickly quench H2O2. It was observed that HHPE decayed away,

with the GLY signal recovering. Similar behavior was observed for HHPA/HHPP formed from

MG and H2O2, as shown in Figure 2.4b. These observations indicate that α-HHPs are equilibrium

products that can regenerate GLY and MG upon quenching of H2O2. To further test the ubiquity

of the formation of α-HHPs and their behavior, we performed the same experiment by adding 13

mM of H2O2 to a 3 mM aqueous solution of propionaldehyde. Formation of a peak at m/z 219 was

confirmed, corresponding to hydroxypropylhydroperoxide, and this compound also reversibly

65

produced propionaldehyde upon quenching of H2O2. This observation further confirms the α-HHP

formation in our system and the generality of this reaction with aldehydes.

From Figure 2.4, the formation and decomposition rate constants of α-HHPs can be roughly

evaluated. The concentration of α-HHPs are estimated from the fraction of GLY or MG that decay

upon addition of H2O2. The second-order rate constant of α-HHP formation from GLY/MG plus

H2O2 is estimated from the initial slope of HHPE and HHPP/HHPA formation (Figure 2.4a,b) to

be 0.06 ± 0.03 M−1 s−1 for GLY plus H2O2 and 0.04 ± 0.02 M−1 s−1 for MG plus H2O2. The kinetics

of HHPE formation from GLY is two orders of magnitude faster than the reported value of another

study (Schone and Herrmann 2014). The reason for such a large discrepancy is unclear. The

decomposition rate constants of α-HHPs forming H2O2 and GLY/MG are determined from the

decay of HHPE and HHPP/HHPA signals after the quenching of H2O2 (Figure 2.4a,b). Both the

HHPE and HHPP/HHPA signals showed first order decays, and the decomposition rate constants

were determined to be 3 × 10−4 s−1 for HHPE and 1 × 10−3 s−1 for HHPP/HHPA.

From the ratio of the formation and decomposition rate constants, the equilibrium constants were

calculated to be 200 M−1 for HHPE and 40 M−1 for HHPP/HHPA, which are comparable to those

that can be estimated from the equilibrium concentrations of α-HHP, H2O2, and GLY, i.e., roughly

40 M−1 for each. The disagreement in the equilibrium constants of HHPE (200 and 40 M−1) using

the two calculation methods demonstrates uncertainties in the approaches used to determine these

quantities. For example, a fraction of the α-HHPs is likely to decompose to re-form GLY and MG

in the heated volatilization line. Also, the decay of the dicarbonyls leads to an estimate of the total

concentration of the α-HHPs forming in each experiment, and not to speciated values. Further

experiments need to be conducted to better determine these rate and equilibrium constants.

Our previous work (Lee et al. 2011) has inferred the formation of α-HHPs during photooxidation

of GLY from the fragmentation pattern of AMS spectra. However, the current study presents the

first direct detection of α-HHPs produced from GLY and MG in the aqueous phase. The fast

response time of Aerosol CIMS and its aqueous-phase detection mechanism using the

volatilization line enabled the detection of α-HHPs, a class of compounds that are otherwise

considered to be unstable and difficult to be detected with offline analytical methods. We are

currently uncertain why others have not identified α-HHPs in their studies.

66

2.3.2 Photooxidation of GLY

Figure 2.5a and b show the decay profiles of GLY and formation of its major products (FA, OA,

GA, and HHPE) from the 3 and 0.3 mM concentration solutions. The organic acid data in the figure

are the average of two to three experimental replicates, and the error bars account for the

fluctuations of the concentration profiles across the experimental replicates. We are unable to

easily quantify the α-HHP species at the moment, so that the HHPE signal from one of the

replicates is shown in Figure 2.5. The H2O2 control experiments of GLY did not result in detection

of any compounds nor in any observable decay of GLY, indicating that the results shown in Figure

2.5 are indeed due to OH driven oxidation.

Figure 2.5: Results of photooxidation experiments with 3 mM (a) and 0.3 mM (b) initial GLY concentration.

Photooxidation was initiated at time 0 (dashed line). Data shown here are the average of 2−3 replicates, and the error

bars represent fluctuations between replicates (1 σ). The signal of 2-hydroxy-2-hydroperoxyethanal (HHPE) overlaps

with that of hydrated GA (GA·1H2O). This normalized signal from one typical experiment is shown (right axis).

The concentration profiles of FA, GA, and OA agree with the mechanism proposed by Lim et al.

(2010), where FA and GA are the first generation products, and OA is a second generation product.

The FA formation before the initiation of photooxidation (Figure 2.5a,b) is due to reaction of H2O2

with impurities in water, which is confirmed from the control experiment, where H2O2 was added

to pure water. Although the formation of GA and OA in the two concentration regimes is

proportional to the initial GLY concentrations, the formation of FA appears to be highly

concentration dependent as shown by the significantly lower production in the 0.3 mM regime

(Figure 2.5a,b), implying the existence of different reaction mechanisms between the two

concentration regimes. We propose that the different behavior in the two concentration regimes is

associated with the α-HHP formation. A recent computational study (da Silva 2011) proposed that

67

an acyl radical of HHPE can decompose to form FA (Figure 2.6, R2.10). These mechanisms are

proposed to occur in the gas phase in the original paper, but formation of acyl radicals due to H-

abstraction reactions is common, and the subsequent decomposition may also occur in the aqueous

phase.

Figure 2.6: Possible formation mechanisms of formic and acetic acids from α-HHPs (from da Silva (2011)).

Formation of α-HHP in the 0.3 mM concentration regime is expected to be less important as

implied from the expression for α-HHP equilibria (Eqn. 2.1):

Kα-HHP = [α-HHP]/([aldehyde] × [H2O2]) (2.1)

where Kα-HHP is the equilibrium constant for α-HHPs in general, and [α-HHP], [aldehyde], and

[H2O2] are the equilibrium concentrations of α-HHP, aldehydes, and H2O2. Because the

concentrations of GLY and H2O2 used in the 3 mM regime were both 1 order of magnitude higher

than those used in the 0.3 mM experiment, Eqn. 1 indicates that the HHPE concentration in the 3

mM case is expected to be 2 orders of magnitude higher. Indeed, the normalized signal of HHPE

in the 3 mM concentration regime (Figure 2.5a) is significantly higher than that in the 0.3 mM

regime (Figure 2.5b). If a significant fraction of FA has been produced from the α-HHP pathway,

the much higher yield of FA in the 3 mM concentration regime can be explained. To further

examine this possibility, we performed an experiment in which HHPE equilibrium was not allowed

to establish prior to the initiation of photooxidation. With HHPE absent at the beginning of the

photooxidation, FA should appear to be a second generation product. The result of this experiment

(Figure 2.7) shows that formation of FA indeed exhibits characteristics of a second generation

product, with slower formation immediately after the initiation of the photooxidation. Lee et al.

(2011) also did not allow HHPE to equilibrate prior to the initiation of photooxidation and observed

68

slow formation of FA at the early stage of photooxidation. This evidence supports the HHPE

pathway of FA formation. By contrast, Lim et al. (2010) suggests that FA is directly produced from

photooxidation of GLY.

Figure 2.7: Three mM GLY photooxidation without α-HHP equilibrium. The experiment was conducted as with the

3 mM GLY photooxidation, except that photooxidation was initiated immediately after H2O2 was added to the GLY

solution at time 0. The error bars represent fluctuations between replicates (1 σ).

As described in the Experimental Methods, the concentration of GLY was estimated using the

signal of GLY·1H2O. The decay of GLY in the 3 mM concentration regime was observed to be

non-first-order and significantly slower than by Tan et al. (2009) and Lee et al. (2011). We propose

that the slow decay of GLY arises via the regeneration of GLY·1H2O from HHPE, as discussed in

detail in the TOC section.

2.3.3 Photooxidation of MG

The time profiles of 3 mM MG photooxidation are shown in Figure 2.8. The data are the average

of two experiments, and the error bars represent fluctuations between the replicates. The signal of

HHPP plus HHPA from one experiment is also shown in the figure. The overall trend of the

photooxidation agrees with the observation of Tan et al. (2010) in that PA, AA, and OA appear to

be the first-, second-, and third-generation (or later) products, respectively, and that the yield of

GA is low. Tan et al. (2010) found the quantification of AA challenging because of its small m/z

(outside of the ESI-MS mass range) and the overlap of AA and GCA peaks in the IC. Here, we

69

successfully quantified AA and GCA using Aerosol CIMS. It is observed that GCA is only a minor

product, whereas AA turns out to be the dominant product of MG photooxidation.

Figure. 2.8: Concentration profiles of MG and its products. Photooxidation was initiated at time 0 (dashed line). The

oxalic acid profile obtained from IC and its fitted line are shown on the graph. Using the fitted line, the MG

concentration profile was calculated. The data represent the average of two independent replicates, with the error bars

showing fluctuation between the replicates (1 σ). The normalized signal of 2-hydroxy-2-hydroperoxypropanal (HHPP)

and hydroxyhydroperoxyacetone (HHPA) from one experiment is shown (right axis).

Note that the yields of FA and AA are observed to be significantly higher than the model prediction

of Tan et al. (2010). Direct photolysis of MG can, at least in part, give rise to the high yields of FA

and AA. A significant amount of FA and AA formation was observed from a H2O2 control

experiment of MG, as shown in Figure 2.9. Approximately 0.4 mM of FA and AA were produced

by 2 h of direct MG photolysis. Tan et al. (2010) did not include direct photolysis of MG into the

model due to the assumption that the effects of direct photolysis are small compared to

photooxidation. This is likely to be true in their experimental setup where the OH radical

70

concentration is 1 order of magnitude higher than in the current study, where we have observed

that FA and AA formation via direct photolysis of MG may be important. In particular, the FA

concentration profile shows rapid formation immediately after the initiation of photooxidation

(Figure 2.9), further implying that this arises from direct photolysis of MG. The higher yield of

AA may also arise by two additional formation pathways associated with α-HHP formation. The

first pathway is PA plus H2O2, as suggested in Stefan et al. (1999): H2O2 reacts with the ketone

group of PA, forming a α-HHP intermediate which decomposes to form AA. The second pathway

is the oxidation of HHPP as illustrated by R2.11 in Figure 2.6 (da Silva 2011). H-abstraction of

the aldehydic hydrogen of HHPP results in an acyl radical which may subsequently decompose to

form AA. The formation of AA is thus complicated, and deconvolution of the relative contributions

is difficult at the moment.

Figure 2.9: H2O2 control experiment for MG. MG solution (3 mM) was exposed to irradiation without addition of

H2O2. The irradiation was initiated at time 0 (dashed line). A significant amount of FA and AA was produced. The

initial increase of the MG signal was due to equilibration of MG in the inlet line, and the initial signal of FA and AA

are due to impurities in solution or due to decomposition of MG prior to the experiment.

As explained previously, OA was quantified by offline IC analysis in the MG photooxidation

experiments. It is known that H2O2 reacts with organic species in the dark to cause secondary

reactions prior to offline analysis, such as FA formation from GA plus H2O2 (Carlton et al. 2007,

Tan et al. 2009) and AA formation from PA plus H2O2 (Stefan and Bolton 1999, Tan et al. 2010).

However, OA is expected to be relatively stable against H2O2 reaction and volatilization loss due

to its low volatility. For these reasons, the offline quantification of OA is expected to be more

71

reliable compared to other organic acids. Indeed, the fitted line from the IC data matched within

10% error the MG·1H2O and OA signal from Aerosol CIMS in the last hour of photooxidation

(Figure 2.10). The excellent agreement between IC and Aerosol CIMS suggests that most of MG

was depleted at the end of photooxidation, and the Aerosol CIMS signal is solely attributed to OA

at this point.

The decay of MG is not first-order, and it appears that a fraction of MG is constantly regenerated

during the photooxidation. This feature is similar to the GLY decay in the 3 mM regime (Figure

2.5a). We propose this observation is also associated with α-HHP formation.

Figure 2.10: Normalized signal of OA (blue) was obtained from the fitted line of IC data. The normalized signal of

MG (yellow) was calculated by subtracting OA normalized signal from total signal of MG + OA (black) obtained

from the Aerosol CIMS.

2.3.4 TOC Concentration and Carbon Balance

The TOC concentrations from 3 mM GLY, 0.3 mM GLY, and 3 mM MG photooxidation

experiments are shown in Figure 2.11a−c. The reconstructed TOC concentrations are calculated as

the total of GLY or MG and their major products. Both the measured and reconstructed TOC

profiles are the average of the experimental replicates. Note that the measured TOC data were not

necessarily obtained from the same experimental replicates of the reconstructed TOC. As shown

in the figures, the measured TOC concentrations constantly decrease, most likely due to formation

of CO2 and volatile species during the photooxidation. The measured TOC profiles in the current

study show excellent agreement with that reported in our previous TOC-AMS study (Lee et al.

2011), confirming the reproducibility of our experimental setup. In all the three experiments

72

conducted, the reconstructed TOC profiles match the measured profiles fairly well (to within 20%),

indicating that Aerosol CIMS detects all the major compounds involved in the photooxidation.

Figure 2.11: Measured and reconstructed TOC concentration in 3 mM glyoxal (GLY) (a), 0.3 mM GLY (b), and 3

mM methylglyoxal (MG) photooxidation experiments. Photooxidation was initiated at time 0 (dashed line). The

measured TOC shows the results from the offline TOC analyzer whereas the reconstructed TOC is calculated from

the total of the quantified organic species (i.e., excluding α-HHPs and oligomers); see text. CIMS data represent the

average of 2−3 independent experimental replicates, and the error bars represent fluctuations between the replicates

(1 σ).

However, note that the reconstructed TOC of 3 mM GLY and MG (Figure 2.11a,c) underestimates

the carbon concentration immediately after the initiation of the photooxidation but better matches

with the measured TOC later on. This initial underestimation of carbon concentration was observed

to be less obvious in the case of 0.3 mM GLY (Figure 2.11b). We propose that the initial

underestimation of carbon concentration is due to α-HHPs, which are excluded from TOC

reconstruction due to the inability to quantify these species. These species convert to compounds

that are considered in the reconstructed TOC in the later period of photooxidation.

It was observed that GLY·1H2O and GLY·2H2O show different decay profiles during

photooxidation (Figure 2.12), with that of GLY·1H2O slower than GLY·2H2O. One possible

73

explanation for this observation is that GLY·2H2O is more reactive to OH radicals because the

bond dissociation energy of a C−H bond on a diol carbon is lower (Ervens et al. 2003). As the

hydration equilibria between GLY·1H2O and GLY·2H2O may not be established instantaneously

(Ervens and Volkamer 2010), a difference in their decay kinetics may arise. Alternatively, a

fraction of α-HHPs may regenerate GLY and MG in the solution during photooxidation. Under a

condition in which aldehydes, H2O2 and α-HHPs are all being consumed, such as during

photooxidation, R-2.1 indicates that the equilibrium is more likely to shift toward the

decomposition of α-HHP. In the case of GLY photooxidation, GLY·1H2O is directly regenerated

from HHPE·1H2O via the reverse reaction of R2.6 (Figure 2.3), compensating a fraction of the

GLY·1H2O decay. However, a significant amount of GLY·2H2O is assumed not to be directly

regenerated because GLY·2H2O is not expected to effectively form α-HHP species (see Figure

2.3). We cannot exclude the possibility that this regeneration of GLY·1H2O also occurs in the

heated volatilization line. The observed slow decay of MG is very likely due to the same

regeneration of MG·1H2O from α-HHPs (R2.9).

Figure 2.12: Decay time profiles of GLY·1H2O and GLY·2H2O during one typical photooxidation experiment. The

α-HHP equilibrium was fully established before the photooxidation was initiated at time 0 (dashed line).

Other deviations between measured and reconstructed TOC may have been caused by the

uncertainties associated with the quantification of GLY and MG. In particular, the different decay

kinetics of GLY·1H2O and GLY·2H2O have caused perturbation in the hydration equilibria of

GLY, making the estimation of total GLY concentration not straightforward.

74

A question arises here: why Lee et al. (2011) underestimated the TOC at the early stage of

photooxidation using coupled AMS and IC measurements, if α-HHPs are indeed converted to GLY

or FA which are detectable by AMS and offline IC analysis? A possible explanation is that the

AMS in Lee et al. (2011) mainly detected the GLY·2H2O form of GLY in solution. Indeed, in the

current study, we found that if the total GLY concentration is estimated by using the GLY·2H2O

signal instead of GLY·1H2O, the decay of GLY is found to be faster and resembles the GLY decay

obtained in Lee et al. (2011). Also, Lee et al. (2011) employed a diffusion drier to dry the generated

particle flow prior to online AMS analysis. Because nonhydrated GLY and GLY·1H2O are more

volatile than GLY·2H2O, they may have partitioned into the gas phase during the drying process

and may not have been detected by the AMS, leading to an underestimation of the TOC

concentration. The arguments above lead to the conclusions that the missing carbon in Lee et al.

(2011) is likely to be the fraction of GLY·1H2O regenerated from α-HHPs in the photooxidation.

2.3.5 Evidence of Oligomer Formation

It is now evident that oligomers, including nitrogen- and sulfur-containing species, are formed via

photochemistry of GLY and MG (Altieri et al. 2006, Carlton et al. 2007, Altieri et al. 2008, Tan et

al. 2009, Galloway et al. 2009, Perri et al. 2009, Tan et al. 2010). Lim et al. (2010) proposed that

oligomerization becomes dominant when initial GLY concentrations exceed the mM level due to

more active radical−radical reactions. From the 3 mM GLY photooxidation experiment, formation

of malonic acid (MA) and succinic acids (SA) was observed using Aerosol CIMS. MA, a C3

diacid, and SA, a C4 diacid, are considered to be oligomers formed during photooxidation. The

observed formation of these two species was significantly lower than the other organic acids, and

their signals are close to the detection limits: 0.002 mM for MA and 0.003 mM for SA. The time

profiles of these two (Figure 2.13) acids imply that SA is formed first, and a fraction of it may have

converted into MA during the photooxidation. This observation agrees with the aqueous-phase

photooxidation mechanism of SA that is described in Gao and Abbatt (2011). We believe that

small concentrations of MA and SA at early times (Figure 2.13, from 0 to 25 min) are due to

contamination carried over from the calibration. Oligomer formation was also observed in 3 mM

MG photooxidation, but MA and SA peaks overlap with those of hydroxypyruvic acid (Altieri et

al. 2008) and mesoxalic acid (Tan et al. 2010), respectively. Oligomer formation was not observed

from the 0.3 mM GLY concentration regime.

75

Figure 2.13: Formation of MA and SA in 3 mM GLY photooxidation.

According to the simulation conducted by Lim et al. (2010), the mass based yield of oligomers

may be around 10% when 3 mM initial GLY concentration is used. With the uncertainties in our

observed and reconstructed TOC, we cannot rule out that 10% of the C resides in an oligomeric

form that we do not observe. Also, it is possible that weakly bound oligomers decompose to smaller

species in the heated transfer line leading to the Aerosol CIMS. However, succinic and malonic

acids are present at low concentrations, representing roughly 1% of the mass. Because Lee et al.

(2010) also did not observe significant oligomer formation, it is possible that the relatively low

H2O2 photolysis efficiency in our system may lead to little oligomer formation; i.e., it is likely that

we do not have sufficient OH radical concentration to bring the reaction into the regime in which

radical−radical reactions, and therefore oligomer formation, are activated.

2.4 Conclusions

Aerosol chemical ionization mass spectrometry (Aerosol CIMS) with the I− reagent ion was used

to monitor aqueous-phase photooxidation of glyoxal (GLY) and methylglyoxal (MG). The major

organic acids produced from photooxidation matched those reported from previous studies.

Oligomer formation was confirmed but was a minor contribution to the total organic carbon (TOC)

concentration. The reconstructed TOC concentrations are in good agreement with directly

measured values, indicating that the current method can simultaneously detect all the major species

involved in the photooxidation of GLY and MG. Having demonstrated the usefulness of Aerosol-

76

CIMS in monitoring a rapidly evolving chemical system in the aqueous phase, we have applied

the Aerosol-CIMS to a more complex chemical system in Chapter 3.

The current study reports the first direct detection of α-hydroxyhydroperoxides (α-HHPs) from

reactions between GLY and MG with H2O2 in the aqueous phase. Significant, rapid α-HHP

formation occurred once H2O2 was added to the GLY or MG solutions in the dark. α-HHPs were

determined to be equilibrium products and can reversibly regenerate GLY and MG upon H2O2

quenching. The equilibrium constants of the α-HHP equilibria with H2O2 and GLY/MG were

calculated to be between 40 and 200 M−1.

α-HHP formation has implications for laboratory studies, and perhaps for some situations in the

ambient environment also. In cloud or fog water, typical concentrations of GLY and MG are at the

range of micromolar levels (Matsumoto et al. 2005) and the H2O2 concentration does not usually

exceed 100 μM (Sakugawa et al. 1990). Under these cloud and fog water conditions, α-HHP

formation is unlikely to be very active. In aerosol, however, Paulson and co-workers (Hasson and

Paulson 2003, Arellanes et al. 2006, Wang et al. 2011) have reported unexpectedly high

concentrations of H2O2. From filter sample analyses and model simulations, they estimated an

average aqueous-phase H2O2 concentration of 70 mM in aerosol liquid water, nearly 3 orders of

magnitude higher than the value predicted from the Henry’s Law partitioning of H2O2 (Arellanes

et al. 2006). It is possible that the unexpectedly high H2O2 concentrations resulted from

decomposition of existing α-HHPs in the aerosol liquid water. Being equilibrium products, α-

HHPs are expected to decompose and regenerate H2O2 upon dilution from the volume of aerosol

liquid water to that of the filter extracts.

The current study has shown that α-HHP formation occurs with aldehydes in general and has

impacts on aqueous-phase chemistry, which are expected to be especially important in aqueous

aerosols where concentrations of H2O2 and aldehydes are high. In particular, photooxidation of α-

HHPs provides an additional formation pathway of FA and AA in addition to previously proposed

mechanisms. α-HHPs may also lead to slower effective loss rates of GLY and MG by regeneration

during the reactions. Finally, α-HHP formation needs to be more systematically investigated to

determine its effects upon partitioning of gases into aerosols in the environment. This study is

presented in Chapter 4.

77

Acknowledgement

We acknowledge the financial support of NSERC and QEIISST. We thank Jennifer Murphy, Milos

Marcovic, Greg Wentworth, and Philip Gregoire for IC support and Edgar Acosta and Shawna

Gao for TOC support.

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84

Chapter 3

Aqueous-phase Photooxidation of Levoglucosan – a Mechanistic

Study Using Aerosol Time-of-Flight Chemical Ionization Mass

Spectrometry (Aerosol ToF-CIMS)

As published in Atmos. Chem. Phys. 14, 9695–9706, 2014. DOI:10.5194/acp-14-9695-2014

Distributed under the Creative Commons Attribution 3.0 License.

85

Abstract

Levoglucosan (LG) is a widely employed tracer for biomass burning (BB). Recent studies have

shown that LG can react rapidly with hydroxyl (OH) radicals in the aqueous phase despite many

mass balance receptor models assuming it to be inert during atmospheric transport. In the current

study, aqueous-phase photooxidation of LG by OH radicals was performed in the laboratory. The

reaction kinetics and products were monitored by aerosol time-of-flight chemical ionization mass

spectrometry (Aerosol ToFCIMS). Approximately 50 reaction products were detected by the

Aerosol ToF-CIMS during the photooxidation experiments, representing one of the most detailed

product studies yet performed. By following the evolution of mass defects of product peaks, unique

trends of adding oxygen (+O) and removing hydrogen (−2H) were observed among the products

detected, providing useful information for determining potential reaction mechanisms and

sequences. Additionally, bond-scission reactions take place, leading to reaction intermediates with

lower carbon numbers. We introduce a data analysis framework where the average oxidation state

(OSc) is plotted against a novel molecular property: double-bond-equivalence-to-carbon ratio

(DBE/#C). The trajectory of LG photooxidation on this plot suggests formation of polycarbonyl

intermediates and their subsequent conversion to carboxylic acids as a general reaction trend. We

also determined the rate constant of LG with OH radicals at room temperature to be 1.08 ± 0.16 ×

109 M-1 s−1. By coupling an aerosol mass spectrometer (AMS) to the system, we observed a rapid

decay of the mass fraction of organic signals at mass-to-charge ratio 60 (f60), corresponding

closely to the LG decay monitored by the Aerosol ToF-CIMS. The trajectory of LG photooxidation

on a f44–f60 correlation plot matched closely to literature field measurement data. This implies

that aqueous-phase photooxidation might be partially contributing to aging of BB particles in the

ambient atmosphere.

3.1 Introduction

Biomass burning (BB) is a major source of atmospheric particles and volatile organic compounds

(VOCs). Directly emitted VOCs and primary organic aerosol (POA) are subject to subsequent

atmospheric processing, leading to formation of secondary organic aerosol (SOA) (Jimenez et al.,

2009). Reliable and quantitative source apportionment is required to understand the effects of BB

on air quality and climate. Apportionment of BB is commonly done using chemical tracers

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(Simoneit, 2002). Levoglucosan (LG) is a widely used particle-phase molecular tracer of BB

(Simoneit et al., 1999), due to its source-specificity and abundance in BB aerosol.

Traditionally, LG has been considered to be highly stable in the atmosphere (Fraser and

Lakshmanan, 2000; Simoneit et al., 2004). Stability is an important requirement for a molecular

tracer as it is a major assumption made in chemical mass balance receptor models commonly

employed for source apportionment (Schauer et al., 1996; Robinson et al., 2006). However, studies

from the past decade have shown that LG is subject to atmospheric loss. For example, the

particulate concentration of LG relative to other BB tracers is lower in the summer than in the

winter, implying an enhanced photo-oxidative decay (Saarikoski et al., 2008; Mochida et al., 2010;

Zhang et al., 2010). Measurements using aerosol mass spectrometry (AMS) have also

demonstrated that the decay of BB organic aerosol signature both in the field and laboratory

experiments is accompanied by a decrease in m/z 60 and an increase in m/z 44 (Grieshop et al.,

2009; Hennigan et al., 2010; Cubison et al., 2011; Ortega et al., 2013).

The decay of LG can be explained by several pathways. Heterogeneous oxidation of LG by gas-

phase oxidants has been studied in the laboratory (Kessler et al., 2010; Hennigan et al., 2010;

Knopf et al., 2011), where it has been demonstrated that particle-phase LG can be oxidized by

hydroxyl (OH) radicals efficiently, leading to LG lifetimes on the order of days. More recently,

gas-phase oxidation has also been proposed to contribute to LG loss (May et al., 2012). A small

fraction of particle-phase LG can volatilize into the gas phase where it is oxidized efficiently. A

third explanation for the observed LG decay is reactive loss in the aqueous phase, such as cloud

water or aqueous aerosol particles. Studies from the past decade have revealed the atmospheric

aqueous phase as an important reaction medium where organic compounds can be processed,

leading to formation and aging of SOA (Blando and Turpin, 2000; Ervens et al., 2011). BB

particles can be hygroscopic, depending on their size and inorganic composition (Petters and

Kreidenweis, 2007; Petters et al., 2009); therefore, a highly functionalized and water soluble

organic species, such as LG, can be subject to aqueous-phase processing. Two laboratory studies

have investigated the kinetics of aqueous-phase OH oxidation of LG (Hoffmann et al., 2010; Teraji

and Arakaki, 2010), finding that OH is the main sink for LG in the tropospheric aqueous phase

with lifetimes on the order of hours. By contrast, little is known of the aqueous-phase reaction

mechanism of LG. The only studies are those of Holmes and Petrucci who investigated acid-

87

catalyzed and OH-induced oligomerization (Holmes and Petrucci, 2006, 2007) and a recent

theoretical study of possible reaction pathways (Bai et al., 2013).

The primary objective of this work is to provide a detailed mechanistic understanding of this

oxidation chemistry, which is needed to incorporate LG photooxidation into cloud water models

and to obtain more insight into the atmospheric processing of BB particles. Additionally, we revisit

the reaction kinetics with OH radicals under conditions relevant to cloud water processing. Aerosol

time-of-flight chemical ionization mass spectrometry (Aerosol ToF-CIMS) is employed to directly

monitor LG and its reaction products in real time, after aerosolization of the reaction solution. In

addition to the powerfulness of Aerosol-CIMS described in Chapter 2, the high mass resolution of

the Aerosol ToF-CIMS enables unambiguous determination of product elemental composition,

and sheds light on fundamental aspects of aqueous-phase photooxidation. We also demonstrate a

novel analysis method, utilizing oxidation state (OSc) and double bond equivalence (DBE), to

obtain functional group information. To relate our results to previous field studies of BB aerosol,

an AMS is employed to connect the chemistry to changes in the AMS signals at m/z 60 and 44.

3.2 Experimental Methods

3.2.1 Solution Preparation and Photooxidation

A solution of LG (1mM) was prepared weekly by dissolving a commercial source (Sigma Aldrich,

99%) in Milli-Q water (18MΩ-cm; total organic carbon (TOC) ≤ 2ppb; ELGAPURELAB Flex).

The reaction solution was prepared prior to each experiment by further diluting the stock solution

in a Pyrex bottle to a volume of either 1L (for the mechanistic study) or 100 mL (for the kinetic

study) with a LG concentration of 10 µM for the mechanistic experiments or 30µM for the kinetic

experiments. H2O2 (Sigma Aldrich, ≥ 30%, TraceSELECT) was added to the solution as the

precursor of hydroxyl (OH) radicals upon irradiation. The concentration of H2O2 was typically

1mM, unless mentioned otherwise. The reaction solution was placed in a cylindrical photoreactor

(Radionex, RMR-200) which supplies UVB radiation from all sides, but not from the top or

bottom. The solution was constantly stirred by a magnetic stir bar, with a fan employed to minimize

solution heating. The solution temperature during photooxidation was approximately 301K. A

series of control experiments was performed to confirm that LG was not directly photolyzed under

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UVB light. A small amount of LG reacted upon H2O2 addition in the dark which did not affect the

results.

3.2.2 Aerosol-ToF-CIMS

The experimental apparatus is illustrated in Figure 3.1. During photooxidation, the solution was

constantly atomized by a constant output atomizer (TSI, model 3076), using compressed air (BOC

Linde, Grade 0.1) as the carrier gas. The particle flow was introduced through Siltek-coated

stainless steel tubing (1/4in. diameter, 70cm long, VWR) heated to 100 or 150◦C. Organic species

in the aqueous droplets evaporated in the heated line and were detected by a chemical ionization

mass spectrometer (CIMS). Volatilization of organic aerosol component for online detection was

first conducted by Hoffmann et al. (1998). Later, Smith and coworkers (Hearn and Smith, 2004)

coupled a heated line to a CIMS instrument and for the first time referred this system as an Aerosol

CIMS. Since then, Aerosol CIMS has been employed to investigate aqueous-phase organic

chemistry (Sareen et al., 2010; Zhao et al., 2012; Aljawhary et al., 2013).

Figure 3.1: The experimental apparatus.

The strength of Aerosol CIMS lies in the fast time response, enabling in situ monitoring of

aqueous-phase chemistry. In the current study, high mass resolution (3000 to 4000ThTh−1 in the

relevant m/z range in V-mode) and excellent detection sensitivity were achieved by employing an

Aerodyne high-resolution time-of-flight chemical ionization mass spectrometer (Bertram et al.,

89

2011). This technique is hereafter referred to as Aerosol ToF-CIMS. For all the experiments, the

ToF-CIMS was operated in V-mode, and the data were analyzed using Tofwerk v. 2.2 on IGOR

platform. To examine the accuracy of elemental assignment, we compared the oxygen-to-carbon

(O/C) and hydrogen-to-carbon (H/C) ratios measured from the LG solution to the theoretical O/C

and H/C of LG, and agreement was observed to be within 10%. More details on the data analysis

are described elsewhere (Aljawhary et al. (2013) and references herein).

Our previous study has shown that Aerosol-ToF-CIMS can target different analyte types through

the choice of reagent ion. Three reagent ions were employed in the current study: protonated water

clusters ((H2O)nH+), iodide water clusters (I(H2O)n

-) and acetate (CH3C(O)O-). The ionization

mechanisms and sensitivity of each of these reagent ions for atmospherically relevant organic

compounds have been summarized in Aljawhary et al. [2013], and are mentioned only briefly here.

(H2O)nH+ can detect organic compounds that have higher proton affinity (i.e. higher gas-phase

basicity) than water clusters ((H2O)n). (H2O)nH+is employed in the kinetic study because it detects

both LG and dimethylsulfoxide (DMSO), the kinetics reference compound (see next section).

I(H2O)n- is employed as the primary reagent ion to study reaction mechanisms because it is

sensitive to a wide spectrum of oxygenated compounds that can form clusters with I-, including

LG and its reaction products. CH3C(O)O- is also employed to study the mechanism and to confirm

the results from the I(H2O)n- experiments. CH3C(O)O- abstracts a proton from compounds that

exhibit higher gas-phase acidity than acetic acid and can selectively detect a variety of organic and

inorganic acids. Occasionally non-acid species (e.g. LG) can also form clusters with CH3C(O)O-.

3.2.3 Mechanistic and Kinetic Studies

Investigation of the reaction mechanism focused on the identification of multiple generations of

reaction products arising during photooxidation using the I(H2O)−n and CH3C(O)O− reagent ions.

The rate constant of LG reacting with OH radicals was determined using the relative rate method,

where the decay of LG is related to that of DMSO, a reference compound with well-known OH

reactivity (see Sect. 3.3.2). A fixed concentration (5µM) of DMSO (Caledon Laboratory

Chemicals, > 99 %) was added to the reaction solution prior to the initiation of photooxidation.

The signals of LG and DMSO were monitored concurrently using Aerosol-ToF-CIMS with

(H2O)nH+ as the reagent ion. The following relationship holds for the decay of LG and DMSO:

90

ln([𝐿𝐺]0

[𝐿𝐺]𝑡) =

𝑘𝐼𝐼𝐿𝐺

𝑘𝐼𝐼𝐷𝑀𝑆𝑂

× ln([𝐷𝑀𝑆𝑂]0

[𝐷𝑀𝑆𝑂]𝑡) (3.1)

where [X]t represents the signal of compound X measured at time t, and kxII represents the second-

order rate constant of X reacting with OH radicals. The relationship in Eqn. 3.1 indicates that

plotting ln([LG]0/[LG]t) against ln([DMSO]0/[DMSO]t) should result in a linear plot, with the

slope representing the ratio of the two rate constants.

The LG concentration used (10 to 30µM) is expected to be similar to cloud water concentrations,

assuming typical organic aerosol loading, LG mass fraction in organic aerosol, and complete

scavenging by a typical cloud water liquid content. Although the H2O2 concentration used in the

experiment is much higher than the ambient level, the steady-state concentration of OH was

estimated to be approximately 2 × 10−13 M from the first-order decay rate of LG. This steady-state

concentration of OH radicals is in the range relevant to cloud water (Jacob, 1986). We believe that

the reaction mechanism investigated in the current study is representative for cloud processing

given that similar reactant concentrations are used as those in cloud water.

3.2.4 Aerosol Mass Spectrometry (AMS) Measurements

In some of the experiments, a stream of the generated particles was also introduced into an

Aerodyne compact time of flight (C-ToF) AMS (Canagaratna et al. 2007) after passing through a

diffusion drier (Figure 3.1). Our previous work has shown that the AMS enables in-situ monitoring

of aqueous-phase photooxidation by measuring non-refractory components in the atomized

solution (Lee et al. 2011, Lee et al. 2012, Aljawhary et al. 2013). The time resolution of the AMS

measurement was 1 min. The data were processed using the AMS data analysis software (Squirrel,

version 1.51H for unit mass resolution data) with a corrected air fragment column of the standard

fragmentation table (Allan et al. 2004).

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3.3 Results and Discussion

3.3.1 Reaction Products and Mechanism

Using the I(H2O)−n reagent ion, roughly 50 reaction products were detected as clusters with iodide,

as described in Appendix A Table A1. The m/z of the products ranged between 173Th and 351Th

(in the form of I− clusters). While Holmes and Petrucci (2006, 2007) observed significant degree

of oligomerization with product m/z up to 1000Th, oligomers of LG were not observed. The

absence of oligomeric products might be due to (1) the initial concentration of LG being lower in

the current study (higher concentrations can facilitate oligomerization, Lim et al., 2010) or (2) the

Aerosol ToF-CIMS setup is not sensitive to oligomers. In our previous study (Aljawhary et al.,

2013), dimers of α-pinene SOA components were detected from aqueous abstract using the same

instrument hence oligomers are likely below the detection limit of the current study. That being

said, we cannot rule out the possibility that oligomers and other low-volatility compounds have

been lost to the wall of the volatilization line, if there are cold spots. Although the volatilization

line is carefully wrapped by a heating tape thoroughly and evenly to minimize cold spots, the inner

wall of the CIMS’s ion-molecular region can potentially be a cold spot because its temperature is

lower. The current study focuses on the discussion of monomeric reaction products which are

detected by the Aerosol ToF-CIMS with better sensitivity.

Overall, the observed products imply that two categories of reaction mechanisms occur in the

reaction system simultaneously: functionalization and bond scission. Functionalization reactions

modify the functional groups on the molecules but do not lead to cleavage of carbon–carbon bonds,

while bond-scission reactions result in carbon–carbon bond breakage.

3.3.1.1 Functionalization – Unique Trends of + O and − 2H

LG is detected at m/z 289 as a cluster with iodide (CH10O5I−). As the LG signal decays, peaks that

are a multiple of 16Th apart from LG (i.e., at m/z 305, 321 and 337) formed rapidly one after

another (Figure 3.2a).

Their elemental compositions are different from each other by one oxygen atom, and this trend is

herein referred to as the “+O” trend. Peaks that are a multiple of 2Th apart from LG (i.e., m/z 287,

285, and 283) are also observed one after another (Figure 3.2b). The elemental composition of

these compounds is different by two hydrogen atoms from each other, and this trend is referred to

92

as the “−2H” trend hereafter. Interestingly, the +O and the −2H trends proceed simultaneously,

forming a series of unique product patterns.

Figure 3.2: The evolution of the “+O” (a) and the “−2H” (b) series from levoglucosan (LG). The signal of each

compound normalized by the reagent ion intensity at m/z 145 (I(H2O)−) is shown as a function of the irradiation time.

The signals are multiplied by the bracketed number to be on scale.

A mass defect plot (Hughey et al., 2001) of the major products detected with the I(H2O)−n reagent

ion clearly illustrates the two trends occurring in the system (Figure 3.3a). Mass defect diagrams

plot mass defect (exact mass−nominal mass) against the exact mass of each compound. Since H

atoms and O atoms have their own mass defects (+0.007825 for H and −0.005085 for O),

compounds that are apart from each other by 2H line up on a slope of 7.77 × 10−3 while compounds

that are apart by an O line up on a slope of −3.18 × 10−4, with the slope denoting the ratio of the

mass defect and the molecular weight. The slopes representing the +2H and the –O trends that are

indicated by the dotted lines in Figure 3.3a. The time at which each peak reached its maximum

level is used to track the order of formation, and is presented by the color code. It can be clearly

seen that multiple +O and −2H trends develop in the reaction system during photooxidation (Figure

3.3a). The maximum signal intensity reached by each peak is used as an indicator of the amount

of formation and is represented by the area of the data points (in log scale). We note that different

compounds exhibit different detection sensitivity to the reagent ion of choice. Aljawhary et al.

(2013) have demonstrated that the I(H2O)−n reagent ion can detect oxygenated compounds with

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carbon numbers of three or more with a relatively constant detection sensitivity. We consider the

signal intensity as a semi-quantitative presentation of the amount of each product.

Figure 3.3: The mass defect diagram of the major products detected using the iodide water cluster (I(H2O)−n) reagent

ion (a). The color code indicates the time at which each compound reached its maximum signal intensity and the area

of the circles represents the maximum signal intensity reached (in log scale). Compounds that did not reach their

maxima during the first 300min of illumination are shown in black. The +O and the −2H series fall on the slope

indicated by the dotted lines. The region relevant to products arising from +O and −2H trends is presented in (b). The

proposed structures of each product are shown beside the data points.

The +O trend must arise from formation of hydroxyl or hydroperoxyl functional groups because

these are the only possible mechanisms leading to addition of oxygen without losing any hydrogen.

Formation of these functional groups in the aqueous phase has been well studied (von Sonntag et

94

al., 1997). The reaction is initiated by H-abstraction and formation of an alkylperoxy radical (RO2).

RO2 can react with another RO2 or a hydroperoxy radical (HO2) to form a tetroxide intermediate

which gives rise to a variety of products (Figure 3.4, R3.1 to R3.3).

Figure 3.4: Sample reaction mechanisms that give rise to the +O and −2H trends. The tetroxide intermediate forming

from two alkylperoxy radicals can result in a variety of products as shown in (R3.1) to (R3.3), among which (R3.1)

can lead to formation of the hydroxyl functional group. A hydroperoxy functional group can be formed from RO2

+HO2 (R3.4). The hydroxyl-to-carbonyl conversion shown in (R3.5) is likely responsible for the −2H trend. Alkoxy

radicals trigger bond-scission reactions and give rise to an aldehydic compound (R3.6).

Among these reaction pathways, R3.1 gives rise to a hydroxyl functional group. When a tetroxide

is formed between RO2 and HO2 radicals (R3.4), a hydroperoxyl functional group can be generated

in analogy to R3.3. The −2H trend in LG photooxidation has been previously reported by Holmes

and Petrucci (2007), likely arising from conversion of hydroxyl functional groups into carbonyl

groups (Figure 3.4, R3.5). When the initial H abstraction occurs from a carbon atom with an

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existing hydroxyl functional group, the subsequently formed peroxy radical leads to formation of

a carbonyl group and releases a HO2 molecule. This study demonstrates that this conversion can

occur multiple times, eventually converting a polyol into a polycarbonyl compound. To confirm

this reaction mechanism, we performed an experiment of aqueous phase photooxidation of another

polyol, erythritol, using the same experimental conditions. The same −2H trend was observed,

consistent with the proposed reaction mechanism. We note that carbonyls can be also formed via

the same mechanism leading to the formation of the hydroxyl functional group (i.e., R3.1 in Figure

3.4). However, formation via this pathway would not lead to the observed −2H trend and is likely

a minor formation pathway of carbonyls compared to R3.5.

The proposed structures of reaction products arising from the +O and −2H trends are included in

Figure 3.3b, which shows a magnified view of the relevant region on the mass defect plot. We note

that the mass spectrometric technique employed in the current work does not allow us to

unambiguously determine the chemical structures. For example, addition of one hydroperoxyl

functional group to a molecule yields the same chemical formula as compared with addition of

two hydroxyl functional groups, and our technique cannot distinguish between these two

mechanisms. Investigation of the formation hydroperoxides could be a direction for future study

since hydroperoxides present a group of highly oxygenated compounds and may alter the reaction

mechanism. Also, some bond-scission reactions can result in chemicals with the same elemental

compositions (see next section). Furthermore, the order in which the hydroxyl groups are

converted to carbonyls is difficult to ascertain. Bai et al. (2013) has demonstrated that H-

abstraction at the middle hydroxyl group of LG is energetically favored.

3.3.1.2 Bond-scission Reactions

Scission of C–C bonds is likely triggered by formation of alkoxy radicals via R2 (Figure 3.4) from

the tetroxide intermediate. Cleavage of one C–C bond gives rise to an aldehyde and an alkyl radical

(R3.6, Figure 3.4). Time series of selected major bond-scission products are shown in Figure 3.5a,

along with their elemental composition and proposed structures. As a general trend, products with

five or six carbons (i.e., products v, vi, vii) form first, followed by those with smaller carbon

numbers as photooxidation proceeds. Using the current mass spectrometric method, it is difficult

to unambiguously determine the structure of these detected species. It is also not possible to

completely rule out the possibility of the fragmentation of large ions in the mass spectrometer,

96

contributing to peaks with smaller m/z. However, the distinct time profiles observed for most of

the products imply that they are independent compounds. The proposed structures have been

estimated from a series of reaction mechanisms shown in Appendix A, Figure A1. The proposed

mechanisms have been constructed based on widely accepted reaction mechanisms, and the

sequence of product formation is consistent with the observed time series.

Figure 3.5: Evolution of bond-scission products measured by the I(H2O)−n reagent ion. Selected major products with

three to six carbons are shown in (a), with their proposed structures. The proposed reaction mechanisms leading to

their formation are attached in Appendix A Figure A1. Formation of small organic acids with one or two carbons are

shown in (b). All the signals have been normalized against the reagent ion (I(H2O)−) at m/z 145.

97

The LG photooxidation reaction system is highly complicated, as demonstrated by the proposed

mechanisms. Multiple reaction pathways can likely lead to the same product, and one chemical

formula may constitute multiple compounds with varying structures. For this reason, the current

work is not intended to determine the complete reaction mechanism but rather to elucidate the

general trend of reactions by monitoring major products detected.

We propose that bond scission may not immediately lead to compounds with fewer carbon

numbers in the case of LG photooxidation. This is because LG contains ring structures, and bond

scission can likely lead to ring cleavage before molecule fragmentation. Formation of product vii

(Figure 3.5a) presents one such example. This bond-scission product has a larger molecular weight

compared to LG. However, product vii overlaps with one of the proposed products in the +O and

−2H series (see previous sections), making it difficult to elucidate its magnitude of formation. In a

study of heterogeneous oxidation of LG and erythritol, Kessler et al. (2010) observed that the mass

loss during LG photooxidation was slower than that from erythritol and also proposed that ring

cleavage in the LG system delayed molecule fragmentation. We suspect that this delay might be

due to formation of compounds such as product vii.

Formation of small organic acids with carbon numbers equal to or less than two are also observed

as later generation products (Figure 3.5b), confirmed by both the I(H2O)−n and the CH3C(O)O−

reagent ion experiments. It is difficult to constrain the explicit formation mechanisms of these

small organic acids because they are likely formed from further photooxidation of the many

intermediate compounds discussed above. For example, it is well known that glyoxal, which is

expected to form as a bond-scission product, forms glyoxylic acid, formic acid, and oxalic acid

(Lim et al., 2010; Lee et al., 2011; Zhao et al., 2012). In particular, oxalic acid exhibited continuous

formation until the end of the photooxidation (Figure 3.5b). This observation agrees with the fact

that oxalic acid is relatively unreactive with OH radicals and presents a relatively long-lived

reservoir of organic carbon in the aqueous phase. We consider the small organic acids as the final

carbon reservoir before they either volatilize from the aqueous phase or are eventually oxidized to

CO2.

98

3.3.1.3 Obtaining Functional Group Information from the Aerosol-ToF-CIMS

As a general trend within the LG system, we hypothesize that a series of compounds containing

multiple carbonyl functional groups may form as reaction intermediates and then are subsequently

oxidized to carboxylic acids. Carbonyl functional groups have likely arisen from (1) the hydroxyl-

to-carbonyl conversion mechanism mentioned in the previous section and (2) bond scission of an

alkoxy radical yielding an aldehyde functional group (R3.6, Figure 3.4). Rapid formation of

carboxylic acids from aldehydes in the aqueous phase has been well documented (Schuchmann

and von Sonntag, 1988; Lim et al., 2010; Zhao et al., 2012). This is a mechanism unique to the

aqueous phase because it is initiated by hydration of an aldehyde or an acyl radical (Scheme 5,

Figure. A1, Appendix A).

Although the Aerosol ToF-CIMS is a powerful tool to elucidate elemental composition, its ability

to reveal functional group information is limited. Here, we present an analysis framework

employing two molecular properties, double bond equivalence (DBE) (Bateman et al., 2011) and

average carbon oxidation state (OSc) (Kroll et al., 2011), which are calculated by Eqn. 3.2 and 3.3:

DBE = #C - #H/2 + 1 (3.2)

OSc = 2 O/C – H/C, (3.3)

where #C and #H represent the numbers of carbon and hydrogen atoms contained in each product

molecule while O/C and H/C represent the oxygen-to-carbon and hydrogen-to-carbon ratios of

each product, respectively. These parameters are readily available from the high mass resolution

analysis of the Aerosol ToF-CIMS. The intensity-weighted average of DBE and OSc from the 50

products monitored by the I(H2O)n- reagent ion (Appendix A, Table A1) are displayed in Figure

3.6. While OSc exhibited continuous increase throughout the entire photooxidation experiment,

DBE exhibited an increase at the beginning but a decrease in the latter half of the experiment. An

increase in DBE can be attributed to formation of (1) carbon–carbon double/triple bonds, (2) ring

structures, or (3) carbon–oxygen double bonds (i.e., C=O in carbonyl or carboxylic acid). Under

an oxidative environment, formation of (1) and (2) is unlikely. Therefore, we conclude that the

initial increase of DBE is due to formation of C=O functional groups in the solution. The later

decrease of DBE is due to molecule fragmentation, making compounds with smaller #C dominate

in the later stages of the photooxidation. To compensate this fragmentation effect, we introduce a

99

novel molecular property, DBE-to-carbon ratio (DBE/#C), which represents the average number

of DBE associated with each carbon. The intensity-weighted average DBE/#C exhibited

continuous increase (Figure 3.6), approaching 1 by the end of the photooxidation experiment. Note

that the theoretical maximum value of DBE/#C is 1. This observation indicates that a C=O double

bond is associated with almost every carbon by the end of photooxidation.

Figure 3.6: Intensity-weighted average of double bond equivalence (DBE), DBE-to-carbon ratio (DBE/#C), and

oxidation state (OSc) as a function of irradiation time.

Although DBE/#C alone cannot distinguish between C=O bonds in carbonyl and carboxylic acid

functional groups, plotting OSc against DBE/#C provides another dimension to the data analysis.

This approach takes advantage of the fact that conversion of a carbonyl (i.e., aldehyde) to a

carboxylic acid involves increase in the molecular OSc, but the DBE/#C remains the same. OSc is

chosen instead of O/C here because O/C is affected by non-oxidative processes, such as hydration

of aldehydes, while OSc is not (Kroll et al. 2011). The trajectory of intensity-weighted average OSc

vs. DBE/#C is shown in Figure 3.7, color coded by the illumination time. During the first 150min

of illumination, both OSc and DBE/#C increase rapidly, leading to a dramatic and linear movement

on the plot with a slope of 3. From 150 to 300min of irradiation, the increases of OSc and DBE/#C

are both slower, but with OSc increasing faster, leading to a slope of 4.3. During the last 150min

of irradiation, DBE/#C stays almost constant at 0.82, close to its theoretical maximum, while OSc

still exhibited slow but continuous increase. The slope during this time period is 9.

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Figure 3.7: OSc vs DBE/#C plot. The intensity-weighted average OSc and DBE/#C from the products listed in

Appendix A Table A1 are displayed here. The color code represents the illumination time. The coordinates of major

compounds are also shown.

This observation is interpreted as observational evidence of polycarbonyl intermediates rapidly

forming in the solution during the early stages of photooxidation, giving rise to rapid increase in

both DBE/#C and OSc. As the illumination reaches 4h, the average DBE/#C reaches 0.8,

indicating the abundance of C=O functional group at this moment. At the final stages of

photooxidation, aldehyde-to-carboxylic acid conversion becomes dominant, leading to a greater

increase in OSc relative to DBE/#C. In addition to the intensity-averaged trajectory, we also added

representative compounds and major products detected during the photooxidation on the OSc vs.

DBE/#C plain (Figure 3.7).

101

Starting from levoglucosan at the left bottom corner, the major products sequentially formed

during photooxidation are located towards the right upper corner of the plot. Oxalic acid, located

at the right upper corner, presents the theoretical maximum for both DBE/#C and OSc. The

averaged trajectory passes through these major products.

Figure 3.8: A simplified overview of reaction mechanisms discussed in the current study. Solid arrows represent

proposed reaction pathways of LG upon OH oxidation. The dashed arrows illustrate the complicity in the reaction

system where each product can also take more than one reaction path.

3.3.1.4 Summary of Reaction Mechanism

As can be seen from the discussion thus far, the reaction mechanisms of the aqueous-phase LG

photooxidation by OH is highly complicated. Figure 3.8 provides a simplified overview of the

mechanisms discussed in the current study. Oxidized by OH, a LG molecule can likely undergo

one of the following reaction pathways: (1) formation of a hydroxyl or hydroperoxyl functional

group, (2) conversion of a hydroxyl group into a carbonyl group, and (3) bond-scission reactions

to form products with reduced carbon number. Among these three pathways, (1) and (2) present

functionalization reactions, and consecutive occurrence of these two pathways has likely given

rise to the observed +O and −2H trends. In fact, each product formed also has the opportunity to

undergo one of the three reaction pathways mentioned above, forming a complicated reaction

system (illustrated by the dashed arrows in Figure 3.8). We propose that multiple OH oxidation

eventually lead to a group of polycarbonyl intermediates that exhibit high DBE/#C values. Further

102

oxidation has likely led to formation of small organic acids, presenting the last organic carbon

reservoir in the aqueous solution.

3.3.2 Kinetic Study

As mentioned in the experimental section, the kinetics of LG photooxidation was investigated

under atmospherically relevant conditions, using DMSO as a reference compound. Both LG and

DMSO decayed rapidly as soon as photooxidation was initiated. Typically, with 0.5mM H2O2 in

solution and over 30min of illumination, LG decayed to 70% of its starting value whereas DMSO

decayed by approximately 80% (Figure 3.9a). Data were plotted in the form of Eqn. 3.1, as

illustrated in Figure 3.9b for one run. Five experiments were performed to determine kLGII (Table

3.1) where the value of kDMSOII , 5.6 × 109 M−1 s−1, was taken to be the average of literature values

(4.5 × 109 to 6.9 × 109 M−1 s−1 (Milne et al., 1989; Bardouki et al., 2002; Zhu et al., 2003). The

concentration of H2O2 was varied between 0.5 and 1.5M, but this variation did not affect the kLGII

value obtained, consistent with the assumption that the concentration of OH is not of relevance to

the relative rate method. The reproducibility of our experiments was excellent, and we report a

value of 1.08 ± 0.16 × 109 M−1 s−1, where the uncertainty reflects the standard deviation of the slope

in the relative kinetic plot.

Table 3.1: Summary of the conditions and the results of the kinetic experiments.

Exp. # [LG] (µM)

[DMSO]

(µM) [H2O2] (mM) kIILG (M-1 s-1)

1 30 5 0.5 8.06 × 108

2 30 5 1 1.10 × 109

3 30 5 1 1.08 × 109

4 30 5 1.5 1.23 × 109

5 30 5 0.5 1.16 × 109

Average 1.08 ± 0.16 × 109

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Hoffmann et al. (2010) have previously reported 2.4 ± 0.3 × 109 M−1 s−1 at 298K while Teraji and

Arakaki (2010) have measured 1.6 ± 0.3 × 109 M−1 s−1 at 303 K, pH 8. Although the kLGII value

obtained from the current work is lower than previously reported, the agreement is reasonable

considering the different methods employed. Hoffmann et al. (2010) used an excess amount of LG

and monitored pseudo first-order decay of OH radicals. Teraji and Arakaki (2010) also used an

excess amount of LG, and calculated kLGII from the observed formation rate of a probe compound.

This study is the first relative rate measurement, using direct measurement of LG.

Figure 3.9: The time series of LG and DMSO during a kinetic experiment (Exp. #1 in Table 3.1) are shown in (a).

The signals are normalized to those at the beginning of the photooxidation. The relative kinetics plot from the same

experiment is shown in (b) according to Eqn. 3.1. The color code indicates the illumination time.

The slower reaction rate observed in the current work can potentially be due to LG desorbing from

the wall of the volatilization line, delaying the decay monitored by the CIMS. LG exhibits

104

substantially lower volatility than DMSO, hence more interaction can be expected between the

wall and the LG compared to DMSO. If the decay of LG has been delayed relative to DMSO due

to wall desorption, the results from the relative kinetic method may be biased. In fact, the diffusion

limited rate constant of LG oxidation by OH radicals in the aqueous phase is estimated by us to be

1.9 × 109 M−1 s−1 (see Appendix A, Sect. A3 for detailed calculations). The results from the two

previous studies are closer to this estimated value, and we consider our result a lower limit of the

reaction kinetics.

3.3.3 Comparison with AMS Data

Decay of LG was accompanied by a decay of f60 monitored by the AMS (Figure 3.10a). The decay

rate of f60 appears slower than that of LG, perhaps due to the fact that compounds other than LG

can also give rise to f60 in AMS. A simultaneous increase in f44 was also observed, indicating

formation of oxygenated compounds such as organic acids, consistent with the proposed

mechanisms mentioned above. The trend of decreasing f60 and increasing f44 closely resembles

that from field measurements of BB particles and heterogeneous oxidation of BB particles in the

laboratory (Cubison et al., 2011; Ortega et al., 2013). Cubison et al. (2011) have demonstrated that

the ratio of f44 to f60 changes in a non-linear manner, approaching a background level of f60 at

0.003, as the photochemical age of the BB air mass increases. Figure 3.10b demonstrates this trend

from the compiled field data in Cubison et al. (2011). Overlayed on this plot is the f44 to f60

trajectory obtained from the current work, color coded by the illumination time, which correlates

nicely with field observations. This agreement is somewhat surprising given that the only reactive

precursor is LG whereas BB particles in the environment contain a complex mixture of organic

compounds. Oxidation of this complex and condensation of gasphase organic acids could also

contribute to an increase in f44. Nevertheless, the current work indicates that aqueous phase

photooxidation can qualitatively lead to similar observations as in the field, contributing to BB

particle aging that arises from other mechanisms such as heterogeneous and gas-phase

photooxidation.

105

Figure 3.10: The decay of levoglucosan monitored by the Aerosol ToF-CIMS and the decay of f60 monitored by the

AMS (a), and the f60 vs. f40 trajectory from the current work compared to field measurements (b). The trajectory

obtained in the current work is color coded with irradiation time. The compiled data (Cubison et al., 2011) from field

measurements in fire plumes (grey) and non-fire plumes (brown) are also shown.

3.4 Conclusions and Environmental Implications

This study presents the first detailed study of levoglucosan (LG) oxidation by OH radicals in the

aqueous phase by online mass spectrometry: aerosol time-of-flight chemical ionization mass

spectrometry (Aerosol ToF-CIMS). Being a soft ionization mass spectrometric technique, Aerosol

ToF-CIMS is extremely useful in elucidating the elemental composition of the reaction products,

106

which sheds light on fundamental chemistry of aqueous-phase photooxidation. This type of

analysis is difficult to perform using hard ionization mass spectrometry.

Functionalization and bond-scission reactions occurred simultaneously in the reaction system.

While bond-scission reactions contributed to formation of smaller organic compounds,

functionalization reactions gave rise to distinct trends of “+O” and “−2H” on mass defect plots.

We propose that these trends arose from formation of hydroxyl and/or hydroperoxyl functional

groups and conversion of hydroxyl to carbonyl functional groups, respectively. As a result, a

compound with multiple hydroxyl functional groups, such as LG, can rapidly yield polycarbonyl

intermediates, representing a general reaction mechanism for polyols.

The current study introduces DBE-to-carbon ratio (DBE/#C) as a novel analysis framework for

high-resolution mass spectrometric data. It is particularly useful in photooxidation because DBE

is most likely arising from formation of C=O in carbonyls and carboxylic acids. The degree of

polycarbonyl formation was observed to be extensive, leading to the average DBE/#C reaching 1

at the end of the photooxidation. As photooxidation proceeds further, these polycarbonyl

intermediates are converted into carboxylic acids, as is inferred from a OSc-to-DBE/#C plot. This

framework can be applied to other soft ionization mass spectrometric techniques with high mass

resolution, providing functional group information.

From the kinetic experiments, the rate constant of LG reacting with OH radical was determined to

be 1.08 ± 0.16 × 109 M−1 s−1, indicating that LG loss due to aqueous-phase photooxidation can be

significant, with a significant portion of LG lost during a typical lifetime of BB particles. This loss

rate should be taken into account when LG is applied as a BB marker in chemical mass balance

receptor models.

Using the AMS, simultaneous decay of f60 and increase in f44 were observed during LG aqueous

oxidation, yielding behavior similar to that observed from field measurements. This observation

qualitatively indicates that aqueous-phase photooxidation may be partially contributing to the

observed decay of LG in the field and observed aging of BB particles.

107

Acknowledgement

The authors thank NSERC for funding, J. L. Jimenez for offering the field data, Aerodyne Inc. for

technical support, and CFI for funding the purchase of the CIMS.

Supplementary Information

Supplementary information of this chapter is given in Appendix A.

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Chapter 4

Formation of Aqueous-phase α-hydroxyhydroperoxides (α-HHP):

Potential Atmospheric Impacts

As published in Atmos. Chem. Phys. 13, 5857–5872. DOI:10.5194/acp-13-5857-2013

Distributed under the Creative Commons Attribution 3.0 License.

114

Abstract

The focus of this work is on quantifying the degree of the aqueous-phase formation of α-

hydroxyhydroperoxides (α-HHPs) via reversible nucleophilic addition of H2O2 to aldehydes.

Formation of this class of highly oxygenated organic hydroperoxides represents a poorly

characterized aqueous-phase processing pathway that may lead to enhanced SOA formation and

aerosol toxicity. Specifically, the equilibrium constants of α-HHP formation have been determined

using proton nuclear-magnetic-resonance (1H NMR) spectroscopy and proton-transfer-reaction

mass spectrometry (PTR-MS). Significant α-HHP formation was observed from formaldehyde,

acetaldehyde, propionaldehyde, glycolaldehyde, glyoxylic acid, and methylglyoxal, but not from

methacrolein and ketones. Low temperatures enhanced the formation of α-HHPs but suppressed

their formation rates. High inorganic salt concentrations shifted the equilibria toward the hydrated

form of the aldehydes and slightly suppressed α-HHP formation. Using the experimental

equilibrium constants, we predict the equilibrium concentration of α-HHPs to be in the µM level

in cloud water, but it may also be present in the mM level in aerosol liquid water (ALW), where

the concentrations of H2O2 and aldehydes can be high. Formation of α-HHPs in ALW may

significantly affect the effective Henry’s law constants of H2O2 and aldehydes but may not affect

their gas-phase levels. The photochemistry and reactivity of this class of atmospheric species have

not been studied.

4.1 Introduction

Recent studies have shown that organic peroxides can be a significant portion of secondary organic

aerosol (SOA) (Bonn et al., 2004; Docherty et al., 2005; Kroll and Seinfeld, 2008). Besides their

contribution to SOA, organic peroxides also damage plant leaves (Polle and Junkermann, 1994),

contribute to acid precipitation by oxidizing SO2 to H2SO4 in the aqueous phase (Lind et al., 1987),

and regenerate OH radicals (Matthews et al., 2005; Monod et al., 2007; Roehl et al., 2007;

Kamboures et al., 2010). α-Hydroxyhydroperoxides (α-HHPs) constitute a class of organic

peroxide that has been observed in the ambient environment. In particular, hydroxymethyl

hydroperoxide (HMP) is the most frequently detected α-HHP in the ambient gas phase (He et al.,

2010), rain water (Hellpointner and Gab, 1989; Sauer et al., 1996), and cloud water (Sauer et al.,

115

1996; Valverde-Canossa et al., 2005), as reviewed by Hewitt and Kok (1991) and Lee et al. (2000).

Other α-HHPs such as 1-hydroxyethyl hydroperoxide, 1-hydroxypropyl hydroperoxide, and bis-

hydoxymethyl hydroperoxide have also been detected in the air or in cloud water, but much less

frequently (He et al., 2010; Lee et al., 1998; Bachmann et al., 1992; Hewitt and Kok, 1991).

Despite their observation in the atmosphere, our understanding of the formation mechanisms of α-

HHP is still incomplete. It has been suggested that the recombination reaction of peroxy radical

(RO2) and hydroperoxy radical (HO2), which is the major formation of organic hydroperoxides in

gas phase, may not be a major formation pathway for α-HHPs (Carter et al., 1979; Atkinson, 1990;

Gab et al., 1995). Instead, other formation pathways, including aqueous-phase reactions have been

proposed (Figure 4.1). The first formation pathway, herein referred to as the Criegee pathway,

involves hydrolysis of the stabilized Criegee intermediate (SCI) generated during alkene

ozonolysis (Lee et al., 2000; Hasson et al., 2003; Ziemann and Atkinson, 2012). The second

pathway involves reversible addition of H2O2 to carbonyls and is herein referred to as the carbonyl

pathway (Hellpointner and Gab, 1989; Zhou and Lee, 1992). The Criegee pathway has gained the

majority of attention because α-HHPs have been observed from laboratory ozonolysis of a variety

of alkenes and monoterpenes (Hewitt and Kok, 1991; Neeb et al., 1997; Sauer et al., 1999; Hasson

et al., 2001; Hasson and Paulson, 2003; Wang et al., 2012). This reaction pathway occurs in both

the gas and aqueous phases, but a few studies (Gab et al., 1995; Chen et al., 2008; Wang et al.,

2012) have shown that aqueous-phase ozonolysis may lead to more efficient formation of α-HHPs

compared to their gas-phase counterparts. In these studies, however, α-HHPs formed in the

aqueous phase dominantly decomposed to H2O2 and aldehydes when analysed under dilute

conditions. The observed rapid decomposition of α-HHPs in such laboratory experiments has lead

to a general perception that α-HHPs are unstable, and are merely a class of intermediates in the

formation of carbonyls and H2O2 during ozonolysis.

However, as shown in Chapter 2, α-HHP formation was observed using advanced mass

spectrometric techniques, arising from H2O2 addition to carbonyl compounds (Lee et al., 2011;

Zhao et al., 2012) and laboratory SOA extract (Liu et al., 2012) using advanced mass spectrometric

techniques. Specifically, in our previous work (Zhao et al., 2012), α-HHP formation from glyoxal

and methylglyoxal with H2O2 was monitored using an iodide (I−) chemical ionization mass

spectrometer coupled to a heated inlet line (Aerosol CIMS). This technique enabled the direct

116

detection and characterization of α-HHPs using online mass spectrometry. In particular, the

formation of αHHPs from glyoxal and methylglyoxal was observed to be fast and reversible, with

equilibrium constants between 40 and 200M−1 for both compounds. As described below, an

equilibrium constant of this magnitude suggests that α-HHPs could be formed in significant

concentrations in aerosol liquid water (ALW) if aldehyde and H2O2 concentrations are high

(Arellanes et al., 2006; Volkamer et al., 2009; Lim et al., 2010). However, the quantification using

Aerosol CIMS is potentially complicated by thermo-decomposition of α-HHPs and unknown

processes involving droplet evaporation in the heated inlet, giving rise to the need for a more

quantitative study using alternative techniques.

We note that although the carbonyl pathway is rarely discussed in the atmospheric chemistry

literature, it has been studied somewhat in the 1940s and 1950s by physical organic chemists using

high precursor concentrations. For example, the formation of α-HHPs has been observed from

several aldehydes (Satterfield and Case, 1954; Sander and Jencks, 1968) and ketones (Milas and

Golubovic, 1959a, b). These early works established the reaction mechanism of the carbonyl

pathway: the reaction proceeds via a nucleophilic addition of H2O2 to a non-hydrated carbonyl

because the carbonyl carbon acts as an efficient electrophile. In particular, Satterfield and Case

(1954) found that the initial rate of H2O2 addition to aldehydes increases in the following order:

formaldehyde < acetaldehyde < propionaldehyde. The explanation for this observed trend is the

difference in the aldehydes’ degree of hydration, with the most hydrated aldehyde (i.e.

formaldehyde) exhibiting the slowest rate of H2O2 addition. This observation leads to their

conclusion that H2O2 addition has to occur on non-hydrated aldehydic functional groups. We also

note that a closely related particle-phase reaction, peroxyhemiacetal formation (Figure 4.1,

pathway 3), which involves nucleophilic addition of an organic hydroperoxide to an aldehyde, has

been previously proposed (Tobias and Ziemann, 2000). As of late, small carbonyls have been

gaining attention as potential SOA precursors via aqueous-phase processing (Ervens et al., 2011).

The formation of α-HHP via the carbonyl pathway may change the physico-chemical properties

of carbonyl-containing SOA in a different way compared to other relatively well known

mechanisms such as OH radical oxidation, thus representing an additional mechanism of aqueous-

phase processing. Once formed in the aqueous-phase, α-HHPs may also react with OH radicals

(Zhao et al., 2012). How this class of compound may alter the reaction mechanisms proposed for

aqueous-phase chemistry is still unclear at the moment.

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Figure 4.1: Two aqueous-phase pathways of α-hydroxyhydroperoxide (α-HHP) formation: 1) The Criegee Pathway,

2) the Carbonyl pathway, and a related reaction 3) Peroxyhemiacetal formation.

Given that the potential of many carbonyls to form αHHPs is currently unknown, the specific goals

of this work were to experimentally determine the equilibrium constants of α-HHP formation via

the carbonyl pathway from a range of atmospherically relevant carbonyl compounds using two

separate analytical methods: proton nuclear magnetic-resonance (1H NMR) spectroscopy and

proton transfer reaction mass spectrometry (PTR-MS). 1H NMR spectroscopy directly quantifies

the chemical changes in the aqueous phase when a carbonyl is mixed with H2O2, and is particularly

well suited for the investigation of thermodynamic equilibria. On the other hand, online PTR-MS

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measurement of the gas-phase concentration of carbonyls after addition of H2O2 provides better

insight into the kinetics of the reactions and can assess the impact of α-HHP formation on the

effective Henry’s law constants (KHeff) of the carbonyls. We note that thermodynamic information

of the type derived in this paper is required to quantify the importance of different derivative

organics in aerosol and cloud water, and yet it is frequently missing from the literature. The paper

concludes with an assessment of the atmospheric importance of α-HHP formation by the carbonyl

pathway.

4.2 Experimental Methods

4.2.1 1H NMR Measurements

The formation of α-HHPs from a suite of atmospherically relevant carbonyl species has been

studied: formaldehyde (Sigma Aldrich, 37 wt% in water with 10–15% methanol as stabilizer),

acetaldehyde (Sigma Aldrich, > 99.5 %), propionaldehyde (Sigma Aldrich, <97%), glycolaldehyde

(Sigma Aldrich, in solid dimer form), glyoxal (Sigma Aldrich, 40 wt % in H2O), methylglyoxal

(Sigma Aldrich, 40 wt % in H2O), glyoxylic acid (Sigma Aldrich, 50 wt % in H2O), methacrolein

(Sigma Aldrich, 95%), methylethyl ketone (ACP Chemicals Inc., 99%), and acetone (EMD,

99.8%). These compounds have low molecular weights and exist largely in the gas phase.

However, several compounds (e.g. glyoxal, methylglyoxal, glyoxylic acid, and glycolaldehyde)

are quite water soluble and can be important aqueous-phase SOA precursors (Carlton et al., 2007;

Altieri et al., 2008; Perri et al., 2009; Ervens and Volkamer, 2010; Lim et al., 2010; Tan et al.,

2010; Ervens et al., 2011; Lee et al., 2011; Ortiz-Montalvo et al., 2012; Zhao et al., 2012).

Aqueous solutions (10 mM) of a targeted carbonyl were prepared individually from the

commercial standards mentioned above. A known concentration (0.5 mM) of dimethylsulfoxide

(DMSO, Fisher Scientific, 99.9%) was added as an internal standard to assist the quantification

and chemical shift calibration. A portion of commercial H2O2 stock solution (Sigma Aldrich, 30%

in water) was also added to the carbonyl solutions shortly after they were prepared at

concentrations usually between 8.9 and 20 mM, but up to 100 mM for ketones and methacrolein

due to insignificant αHHP formation from these species. A 500µL aliquot of the mixed solution

was transferred into a 500µL glass NMR tube along with 25 µL of D2O (Cambridge Isotope

Laboratories, Inc., 99.96%) as a lock reagent for the 1H NMR measurement. Using an autosampler

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(Bruker B-ACS 120), 1H NMR spectra were acquired with a Bruker Avance 500 MHz

spectrometer using a 1H, 19F, 13C, 15N 5 mm quadruple resonance inverse (QXI) probe fitted with

an actively shielded Z gradient. 1H NMR experiments were performed with presaturation using

relaxation gradients and echoes (PURGE) (Simpson and Brown, 2005) water suppression and 128

scans, a recycle delay of 3s, and 16K time domain points. Spectra were apodized through

multiplication with an exponential decay corresponding to 0.3Hz line broadening in the

transformed spectrum and a zero filling factor of 2, then manually phased and calibrated to the

DMSO at 2.5ppm. The recycle delay was set at 5 times the measured T1 to ensure full relaxation

between scans. Spectral predictions were performed in Advanced Chemistry Development’s

ACD/SpecManager using a neural network prediction algorithm (version 12.5). All calculations

were performed using water as the solvent with a spectral line shape 2Hz chosen to match those

of the real datasets as closely as possible.

For most of the samples, the 1H NMR spectra were taken within 24h after the samples were

prepared, and within 48h for a small number of samples. The time scale of α-HHP equilibration is

30 to 60min (confirmed in the PTR-MS experiments), so the equilibria should be fully established

when 1H NMR spectra are taken. The sample solutions were no longer protected from room light

once loaded on the autosampler. To examine potential evaporation of carbonyls and OH generation

from H2O2 photolysis, some methacrolein samples were analysed a second time 10 hours after the

first measurement. Methacrolein was chosen because it is the most volatile aldehyde studied here

(Allen et al., 1998) and is highly reactive to OH radicals (Herrmann et al., 2010). The concentration

of methacrolein did not show observable change before and after 10 hours of room light exposure,

and so it is assumed that evaporative loss and room-light exposure induced negligible effects to

other samples as well.

The temperature inside the NMR instrument was controlled at 25◦C. A NMR tube typically stayed

inside the instrument for 20 min for the homogenization of its magnetic field before the spectra

were acquired. Water blanks and control experiments were performed to ensure that the peaks in

the spectra are not from H2O2 reacting with water impurities or DMSO. The effect of pH was not

examined. Previous studies reported that acid can catalyse the rate of α-HHP formation and

decomposition, but does not affect the equilibria (Marklund, 1971; Zhou and Lee, 1992).

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4.2.2 Effects of Inorganic Salts

Aerosol liquid water (ALW) can contain high concentrations of inorganic salts up to and beyond

their saturation concentrations (Tang et al., 1997), making it important to investigate the effect of

high concentrations of aqueous-phase inorganic salts on the equilibria. To do this, 1 M of either

(NH4)2SO4 (AS) or Na2SO4 (SS) was added to a number of acetaldehyde and glycolaldehyde

samples. The NMR probe used in the current method is not compatible with any higher salt

concentrations. The salts were added after the α-HHP equilibrium had been fully established.

4.2.3 PTR-MS Measurements

To confirm the equilibrium constants determined by 1H NMR spectroscopy and further investigate

the effects of these condensed-phase equilibria to the KHeff of the carbonyls, a setup involving a

bubbler and a PTR-MS (Ionicon Analytik, quadruple mass spectrometer) was used, as shown in

Figure 4.2. This system was used to measure the effect of H2O2 addition to the gas-phase mixing

ratio of the carbonyls.

Figure 4.2: Experimental setup for the PTR-MS measurements.

Ultra-pure N2 (BOC Linde, grade 4.8) was introduced to a temperature-controlled glass bubbler

containing an aqueous solution (10 mM) of a carbonyl compound. The gas-phase carbonyl loading

exiting the bubbler was measured by the PTR-MS after dilution (2 to 3 lpm) with ultra-pure N2.

The bubbler was placed in the dark during experiments to minimize light exposure. Teflon lines

and connections were used downstream of the bubbler to minimize surface reactions and loss of

carbonyls. N2 was continuously introduced through the carbonyl solution until a stable PTR-MS

121

signal was achieved at the mass-to-charge ratio (m/z) of the protonated carbonyl. A known

concentration of H2O2 (typically 8.9 to 17.7 mM) was then added to the bubbler, and the N2 flow

was resumed until the PTR-MS signal reached a new equilibrium. Equilibrium constants were

determined from the difference of the carbonyl signals detected before and after the H2O2 injection.

With the detection limit set by the PTR-MS, this approach could be used only for sufficiently

volatile carbonyls: acetaldehyde, propionaldehyde, methacrolein, methylethyl ketone, and

acetone. The experiments were typically performed at 25 ◦C except for those with acetaldehyde

reaction giving rise to the formation of 1-hydroxyethyl hydroperoxide (1-HEHP), which were

conducted also at 15 and 5 ◦C.

4.2.4 Reversibility Test: Addition of Catalase

In both the NMR and PTR-MS experiments, catalase from bovine liver was added to the reaction

mixture to react away H2O2 to test the reversibility of the reaction. In our previous study (Zhao et

al., 2012), quenching of H2O2 led to the decomposition of α-HHPs and regeneration of the original

aldehydes. For the 1H NMR experiments, 1 µL of the catalase solution (Sigma Aldrich, 34 mg

protein mL−1) was added to 1mL of the carbonyl-H2O2 reaction mixtures after the equilibrium was

fully established. Control experiments were performed to confirm that there was no contribution

of catalase to the 1H NMR spectra. For the PTR-MS experiments, one drop of catalase was added

to the 25mL reaction mixture after the equilibrium was fully established. The N2 flow was resumed

after the catalase addition, and the change of the carbonyl signals was monitored. Control

experiments demonstrated that catalase did not cause any change in the PTR-MS signal at the m/z

of interest.

4.3 Results and Discussion

4.3.1 1H NMR Results

With the exclusion of methacrolein, significant changes in the 1H NMR spectra were observed for

all the aldehydes upon addition of H2O2 to the carbonyl solution, with the magnitude of the change

increasing with the concentration of H2O2. The reactions were also observed to be largely

reversible from the catalase addition experiments. As described below, the formation of α-HHP

from acetone and methylethyl ketone was observed to be minor. Spectral assignment was based

122

on manual interpretation and comparison to standards, followed by confirmation using spectral

prediction.

Figure 4.3: 1H NMR spectra for acetaldehyde. (a): Acetaldehyde aqueous solution; (b): 17.7 mM of H2O2 was added

to the acetaldehyde solution; (c): Catalase was added to the solution to quench H2O2. The insets are the magnified

view of certain regions of the spectra. The split pattern and the identity of each peak are shown in the brackets (the

numbers match those in the chemical structures).

The experiment involving acetaldehyde is shown in Figure 4.3 as an example. Before the addition

of H2O2, acetaldehyde and its hydrated gem-diol coexist in the solution (Figure 4.3a). Based on

their chemical shift and splitting patterns, the identities of the peaks are assigned and labelled.

After addition of 17.7 mM of H2O2 (Figure 4.3b), two new peaks appeared at chemical shifts 5.06

and 1.06ppm, respectively, corresponding to the V and VI protons in 1-HEHP. It is not surprising

that the two new peaks appeared very close to the peaks of hydrated acetaldehyde (i.e. the III and

5

4

3

2

1

0

x10

6

10 8 6 4 2 0 -2

Chemical Shift (ppm)

2.0x106

1.5

1.0

0.5

0.0

Sig

na

l In

ten

sity (

AU

)

2.0

1.5

1.0

0.5

0.0

x10

6

5.10 5.00

Chemical Shift (ppm)

5.10 5.00

Chemical Shift (ppm)

5.10 5.00

Chemical Shift (ppm)

1.10 1.00

Chemical Shift (ppm)

1.10 1.00

Chemical Shift (ppm)

1.10 1.00

Chemical Shift (ppm)

(I, q)

(III, q) (IV, d)

(DMSO, s)

(II, d)

(I, q)

(I, q)

(III, q)

(III, q)

(DMSO, s)

(DMSO, s)

(II, d)

(II, d)

(IV, d)

(IV, d)

H2O

H2O

H2O

(V, q) (VI, d)

From Catalase

From Catalase

a)

b)

c)

123

IV protons), given the similar structure between hydrated acetaldehyde and 1HEHP. The

reversibility of the reaction was confirmed upon addition of catalase (Figure 4.3c), with the spectra

then resembling those at the start of the experiment.

Figure 4.4: Hydration equilibrium constant (Khyd), the α-HHP formation equilibrium constant (Keq) and the apparent

α-HHP formation equilibrium constant (Kapp). Please see the text for details.

The water peak was very large in each spectrum even with the water suppression procedures, such

that some overlapping analyte peaks complicated their peak assignment and quantification. For

peaks partially overlapping with water (e.g. at 5.04 ppm in Figure 4.3), baseline corrections were

performed before quantification. Also, we note that the gain of each NMR spectrum was auto-

adjusted by the instrument so that the quantification of compounds had to be conducted by

comparing the analytes’ peak area and number of protons (#H), with signals arising from 0.5 mM

of DMSO added as the internal standard. The calculation was performed in the following manner

(Wallace, 1984):

Concentration of analyte (M)

Concentration of Internal Standard (M)

=Peak area of analyte

Peak area of internal standard×

#Hinternal standard

#Hanalyte (4.1)

Based on the quantified concentrations, we calculated three equilibrium constants: the hydration

equilibrium constant (Khyd), equilibrium constant for α-HHP formation (Keq), and the apparent

124

equilibrium constant for α-HHP formation (Kapp). The relationship between the three constants is

illustrated in Figure 4.4, and their definitions are below:

Khyd =[Carbonylhyd]eq

[Carbonylnon−hyd]eq (4.2)

Keq =[α−HHP]eq

[H2O2]eq ×[Carbonylnon−hyd]eq (4.3)

Kapp =[Total α−HHP]eq

[H2O2]eq ×[Total Carbonyl]eq (4.4)

where [Carbonylhyd]eq and [Carbonylnon-hyd]eq represent the equilibrium concentrations of the

hydrated form and the non-hydrated form of a carbonyl, respectively. The hydration equilibria of

many atmospherically relevant carbonyls are well studied, and so, comparing our results to the

literature values is a good way to verify our 1H NMR method. In Eqn. 4.3, [α-HHP]eq and

[H2O2]eq represent the equilibrium concentrations of an α-HHP and H2O2.. The usefulness of the

Keq defined this way is, however, limited especially for dicarbonyls such as methylglyoxal that can

form multiple α-HHP equilibria. Unambiguous determination of all the Keq values is also

impossible because some of the peaks are missing due to overlap with the water peak. Kapp, on the

other hand, is a better indicator for the overall potential of α-HHP formation from each carbonyl

compound. The [Total α-HHP]eq and [Total Carbonyl]eq in Eqn. 4.4 represent the summed

equilibrium concentrations of α-HHPs and carbonyls (i.e. hydrated and non-hydrated forms),

respectively. Given that the Khyd values did not change with the H2O2 addition, [Total Carbonyl]eq

can be estimated from determination of the concentration of either the hydrated or non-hydrated

form of the carbonyl. Thus the use of Kapp negates the need for unambiguous assignment of all the

peaks. We also note that Eqn 4.2 to 4.4 indicate that Kapp and Keq / Khyd should be essentially equal

if the aldehydes exist mostly in the hydrated form. We have used this relationship as an

125

independent confirmation of our measurement reliability (see Sect. 4.3.3). The measured Khyd and

Kapp values of the carbonyls using 1H NMR are tabulated in Table 4.1 and Table 4.2, respectively,

along with values from the literature. The determined Keq values are reported in Table B1 in

Appendix B.

Table 4.1: Summary of hydration equilibrium constants (Khyd) measured by NMR. The constants are reported with

their standard deviation arising from the number of replicates indicated on the table.

NMR (this work) a Literature

Khyd # replicates Khyd

Formaldehyde b >18 14 2.3 × 10

3 [1]

Acetaldehyde 1.43 ± 0.04 15 1.43 [2]

Propionaldehyde 1.26 ± 0.13 16 0.7 [2]

Glycolaldehyde 16.0 ± 1.3 16 10 [3]; c 17.5 [4]

Methacrolein b <0.005 16 -

Glyoxal d n.d. 16 2.2 × 10

5 [5]

Methylglyoxal b >57± 155 16 2.3 × 10

3 [5]

Glyoxylic acid b >18 16 3000 [6]

Acetone b <0.002 2 0.002 [7]

Methylethyl ketone b <0.005 6 -

a References used: [1] Betterton and Hoffmann, 1988; [2] Greenzaid et al., 1967; [3] Sorensen, 1972; [4] Yaylayan et

al.. 1998; [5] Wasa and Musha, 1970; [6] Sorensen, 1974; [7] Bruice et al., 2004

b Calculated using the limit of quantification of the current methods.

c In D2O.

d n.d.: The value is not determined due to overlapping of analyte peaks with the water peak.

126

Table 4.2: Summary of the apparent equilibrium constants of α-HHP formation (Kapp) measured and reported in

literature at 25 ˚C. The constants are reported with their standard deviation acquired from the number of replicates

shown on the table.

NMR Measurement PTR-MS Measurement a Literature

Kapp

(M-1)

#

Replicates

Catalase

Recovery

(%)

Kapp

(M-1)

#

Replicates

Catalase

Recovery

(%)

Kapp

(M-1)

Formaldehyde

b 164 ± 31 12 c

p.o. d n.p. n.p. n.p.

126 [1]

150 [2]

94 [3]

Acetaldehyde 94.8 ± 12.5 11 97 ± 1 132 ± 15 8 95.8 48 [3]

Propionaldehdye 51.1 ± 8.0 12 83 ± 3 84 ± 12 8 85 -

Glycolaldehyde 43.3 ± 3.9 12 89 ± 4 n.p. n.p. n.p. -

Methacrolein 0.8 ± 0.7 12 n.p. en.d. 6 n.p. -

Glyoxal n.d. 12 p.o. n.p. n.p. n.p. 40 - 200 [4]

Methylglyoxal f 25 ± 4 12

g 85 n.p. n.p. n.p. 40 - 200 [4]

Glyoxylic acid f440 ± 270 13

g78 n.p. n.p. n.p. -

Acetone h <0.008 2 n.p. n.d. 6 n.p. -

Methylethyl

ketone h <0.02 6 n.p. n.d. 4 n.p. -

a References used: [1] Marklund, 1972; [2] Zhou and Lee, 1992; [3] Kooijiman and Ghijsen, 1947; [4] Zhao et al.

2012

b Including the formation of BHMP (see text).

c p.o.: Values could not be determined due to peaks overlapping with the H2O peak.

d n.p.: Experiment not performed.

e n.d. Not detected at the current detection limit of PTR-MS.

fA significant amount of formic acid was observed. The Kapp value is determined with the consideration of irreversible

formic acid formation.

g A decreasing trend of the recovery with increasing concentration of H2O2 addition.

h Calculated using the limit of quantification of the current methods.

127

4.3.2 PTR-MS Results

Acetaldehyde, propionaldehyde, methacrolein, acetone, and methylethyl ketone were detected in

their protonated form at m/z 45, 59, 71, 59, and 73, respectively. Besides their protonated

molecular ions, three other major fragment ions at m/z 31, 39, and 49 were detected from

propionaldehyde, and one major fragment ion at m/z 55 was detected from methylethyl ketone.

For these two carbonyls, the total signal intensity of the protonated molecular ion and the major

fragments were used for quantification. No α-HHP signal was detected using the current PTR-MS

method.

Figure 4.5 illustrates data from a sample experiment for acetaldehyde at 25◦C. Acetaldehyde signal

normalized to the H3O+ reagent ion became stable 20 min after a 10 mM solution was placed in

the bubbler at time (i). After 17.7 mM of H2O2 was injected into the solution at time (ii), the

acetaldehyde signal decreased and rapidly reached a new equilibrium due to the formation of 1-

HEHP in the solution. Upon addition of catalase at time (iii), the acetaldehyde signal recovered

close to its original level. A similar trend was observed for propionaldehyde, but methacrolein,

acetone, and methylethyl ketone did not show any observable change upon H2O2 addition.

Figure 4.5: Sample time series of signal due to gas-phase acetaldehyde in the PTR-MS experiment. The acetaldehyde

signal normalized to the reagent ion is shown as a function of time. Time (i): 25 mL of clean water in the bubbler is

replaced by 25 mL of acetaldehyde solution (10 mM), Time (ii): 13.3 mM of H2O2 is added to the acetaldehyde

solution, Time (iii): one drop of catalase stock solution is added.

128

The equilibrium constants of α-HHP formation from acetaldehyde and propionaldehyde were

calculated from the difference in their signals before and after H2O2 addition (Table 4.2). The Kapp

values defined in Eqn. 4.4 are calculated by using the aldehyde signal after the H2O2 addition as

[Total Carbonyl]eq, the magnitude of change in the aldehyde signal as [Total α-HHP]eq, and the

difference between the total H2O2 concentration and [Total α-HHP]eq as [H2O2]eq. The calculation

of Kapp here is based on assumptions that (1) the non-hydrated forms of acetaldehyde and

propionaldehyde detected by the PTR-MS are proportional to their total concentrations in the

solution (i.e. their Khyd values remain constant), and (2) their signal change is solely due to α-HHP

formation. The first assumption is verified by the observation from the 1H NMR experiments that

Khyd values stayed constant regardless of the amount of H2O2 addition.

The validity of the second assumption is challenged by irreversible processes potentially occurring

in the system, such as oxidation reactions induced by H2O2 and volatilizational loss of the

aldehydes due to bubbling. To examine formation of irreversible products, particularly organic

acids, the PTR-MS was operated under the scan mode (m/z 20 to 120), but no change was observed

in the mass spectra aside from the decay of the protonated molecular ion and major fragments.

Additionally, the recovery of acetaldehyde and propionaldehyde were observed to be 96 and 85

%, respectively (Table 4.2). The high recovery illustrates that the reaction is mostly reversible due

to α-HHP formation. The volatilizational loss of acetaldehyde and propionaldehyde from pure

solutions at 25 ◦C over two hours of bubbling could be up to 11 and 14%, based on the flow rate

of N2 through the bubbler, the solution volume, concentration, and the Henry’s law constants (KH)

of the two aldehydes.

4.3.3 Comparison of Equilibrium Constants

In general, the Khyd values showed good agreement with values from the literature (Table 4.1), and

the Kapp values determined from the two methods reasonably agreed with each other and with the

literature (Table 4.2). The agreement between Kapp and Keq/Khyd was good (Appendix B, Table B1)

for acetaldehyde, propionaldehyde, and glycolaldehyde, but the values of formaldehyde showed a

deviation of more than a factor of 4 (see discussion for formaldehyde below). The inability of

methacrolein, acetone, and methylethyl ketone to form α-HHP was confirmed from both methods.

Formic acid formation was observed upon H2O2 addition to methylglyoxal and glyoxylic acid.

129

Detailed discussion of results for each compound is provided below, and an example 1H NMR

spectra for each compound is provided in Appendix B.

4.3.3.1 Formaldehyde

The equilibrium concentration of formaldehyde was calculated by subtracting the amount of

hydroxymethyl hydroperoxide (HMP) observed (Figure 4.6, proton III) from the total

concentration of 10 mM. In particular, the Khyd of formaldehyde is so large that the aldehydic

proton peak (proton I) was below the 1H NMR detection limit, which is determined to be

approximately 100 µM. This observation is supported by the large Khyd value in the literature: 2.3

× 103 (Betterton and Hoffmann, 1988). The methylene proton peak (II) was also not observed in

the 1H NMR spectra likely due to overlap with the water peak.

We propose that the small peak that appeared at 4.94 ppm is due to formation of bis-hydroxymethyl

hydroperoxide (BHMP, proton IV). This peroxyhemiacetal compound forms by HMP further

reacting with non-hydrated formaldehyde. BHMP has been observed in a number of laboratory

studies (Marklund, 1971; Zhou and Lee, 1992; Gab et al., 1995) and in the atmosphere (He et al.,

2010). The Kapp for BHMP formation (Kapp,BHMP) is calculated by Eqn. 4.5,

Kapp,BHMP =[BHMP]eq

[HMP]eq ×[Total Carbonyl]eq (4.5)

to be 12.0 ± 1.3 M−1 (where the uncertainties are precisions derived from a number of replicates),

showing excellent agreement with two reported values: 11.7 M−1 from Zhou and Lee (1992) and

14.0 M−1 from Marklund (1971). The overall Kapp value for formaldehyde is determined to be 164

± 31 M−1. This value is slightly larger than the three literature values reported because those values

are for only HMP formation, while the value in this work incorporates BHMP formation.

The deviation between Kapp and Keq/Khyd was larger compared to acetaldehyde, propionaldehyde,

and glycolaldehyde (Appendix B, Table B1). We are not entirely sure about the reason for this

deviation, but it could be due to the fact that we used a Khyd value from the literature not measured

in our own system, and/or that formaldehyde forms BHMP beside HMP and exhibits a more

complicated reaction pathway.

130

Figure 4.6: 1H NMR spectra of a formaldehyde-H2O2 mixture. The splitting pattern and assignment of the peaks are

shown in the bracket.

4.3.3.2 Acetaldehyde

The Khyd value, 1.43 ± 0.04, agrees very well with the reported value (Greenzaid et al., 1967). Our

measured value of Kapp, 94.8 ± 12.5 M−1, is larger than the only literature value by a factor of 2

(Kooijman and Ghijsen 1947). The results from the PTR-MS, 132 ± 15 M−1, showed reasonable

agreement with the 1H NMR results.

8x106

6

4

2

0

Sig

nal In

tensity (

AU

)

5.0 4.5 4.0 3.5 3.0 2.5 2.0

Chemical Shift (ppm)

BHMP (IV, s)

HMP (III, s)

H2O

(methanol, s)

(DMSO, s)

131

4.3.3.3 Propionaldehyde

The experimental Khyd value, 1.26 ±0 .13, was slightly larger than the reported value 0.7 (Greenzaid

et al., 1967). The agreement between the 1H NMR and the PTR-MS measurements was fair, with

the Kapp value determined to be 51.1 ± 8.0 and 84 ± 12M−1, respectively. The catalase recovery was

83 ± 3 and 85 %, respectively.

4.3.3.4 Glycolaldehyde

Glycolaldehyde solutions were prepared by dissolving glycolaldehyde dimer (2,5-dihydroxy-1,4-

dioxane) in water. The major peaks in the 1H NMR spectra were from glycolaldehyde monomers,

indicating that monomerization proceeds almost to completion in the solution at the current

concentration used (Yaylayan et al., 1998; Glushonok et al., 2000). The observed Khyd value, 16.0

± 1.3, fell into the same range as several other reported Khyd values (Sorensen, 1972; Yaylayan et

al., 1998). There are no prior reports of the equilibrium constant of α-HHP formation.

4.3.3.5 Methacrolein

Among the carbonyl compounds studied, methacrolein was the only aldehyde that did not show

significant α-HHP formation, as confirmed by both the 1H NMR and PTR-MS studies. The Kapp

was determined to be 0.8 ± 0.7 M−1 from the 1H NMR, but no observable α-HHP formation was

observed using PTR-MS. We propose that the carbonyl group and the C=C double bond in

methacrolein form π-electron conjugation which stabilizes the aldehyde from nucleophilic attacks.

Although Claeys et al. (2004) proposed a mechanism of polyol formation from methacrolein and

H2O2 in the particle phase (Claeys et al., 2004), no such products were observed in the current

experiment.

4.3.3.6 Glyoxal

No quantitative data for glyoxal could be acquired from the current study. In particular, the PTR-

MS is not highly sensitive to glyoxal, and most of the glyoxal peaks in the 1H NMR spectra were

hidden behind the water peak. The only literature value for Kapp of glyoxal is from our previous

work (Zhao et al., 2012), where we estimated the lower limit of Kapp to be 40 M−1 using an Aerosol

CIMS.

132

4.3.3.7 Methylglyoxal

Hydration and α-HHP formation occurring on one or both of the carbonyl groups in methylglyoxal

would lead to a slightly different chemical environments for the protons, making the 1H NMR

spectra of methylglyoxal highly complicated. We performed peak assignment based on the

predicted chemical shift of each proton by spectra prediction and on changes in the peak intensity

upon H2O2/catalase additions, but the peak assignment for methylglyoxal is associated with a

higher level of uncertainty than with the other molecules. A non-negligible amount of formic acid

formation was also observed with H2O2 addition (8.2 ppm, Figure B2 in Appendix B). Formic acid

likely forms irreversibly, as shown by a decreasing trend in catalase recovery, 91, 87, and 84%,

with increasing amount of H2O2 addition: 10, 15, and 20 mM. We assumed that formic acid

formation was slow compared to the α-HHP formation equilibrium, such that Kapp can still be

calculated from the amount of α-HHP formed and methylglyoxal remaining. This way, the Kapp

value is determined to be 25 ± 4 M−1. This value falls below the range of our previous estimation:

40–200 M−1 (Zhao et al., 2012). The discrepancy between the two studies may be explained either

by the uncertainties associated with the Aerosol CIMS method (see Introduction), or by the

methylglyoxal peak assignment here.

4.3.3.8 Glyoxylic Acid

The 1H NMR spectra of glyoxylic acid solutions indicates that it exists mostly in its hydrated form,

qualitatively agreeing with its large reported Khyd value (3 × 103, Sorensen et al., 1974). Upon H2O2

addition, a significant amount of formic acid formation (8.1ppm, Figure B5 in Appendix B) – up

to 50 % of the total glyoxylic acid – was observed. Irreversible formic acid formation from

glyoxylic acid and H2O2 in the aqueous phase is well documented (Tan et al., 2009; Lee et al.,

2011; Ortiz-Montalvo et al., 2012). We propose that at least some of the glyoxylic acid exists in

its α-HHP form because the decay of glyoxylic acid was larger than the amount of formic acid

formation, and some of glyoxylic acid was regenerated with catalase addition. However, a reliable

quantification of the Kapp value is highly challenging, as reflected by the large uncertainties in the

reported value (440 ± 270 M−1).

133

4.3.3.9 Acetone and Methylethyl ketone

The two ketones studied did not exhibit significant α-HHP formation in either the 1H NMR or the

PTR-MS experiments. In general, ketones are known to be relatively stable against nucleophilic

addition as compared to aldehydes. This is because the additional alkyl group stabilizes the

carbonyl functional group via electron donation. Such a trend can be also seen from the small Khyd

reported for ketones (e.g. 2.0 × 10-3 for acetone, Bruice, 2004). The unstable nature of α-HHPs

from ketones has also been reported previously (Sauer et al., 1999; Wang et al., 2012). However,

we note that these simple ketones do not fully represent the diversity of ketones in SOA. In fact,

the current work and past studies have implied α-HHP formation on the ketone group of

methylglyoxal (Stefan and Bolton, 1999; Zhao et al., 2012).

4.3.4 Temperature Dependence of Kapp

We observed enhanced 1-HEHP formation from acetaldehyde with decreasing temperature, but

with slower reaction rates. Example data are shown in Figure 4.7a. The ratio of acetaldehyde signal

to its initial level at 5, 15, and 25 ◦C is plotted as a function of time. The injection of H2O2 (13.3

mM) was performed at time (i). The time required for equilibration was approximately 1, 2, and 5

hours at the three temperatures. The signal level at equilibrium, determined by fitting an

exponential function to the signal, decreases with decreasing temperature, as indicated by the

horizontal dashed lines in Figure 4.7a. The temperature dependence observed here implies more

significant α-HHP formation at colder temperatures. The Kapp values determined at the three

temperatures are listed in Table 4.3. From a van’t Hoff plot of these data (Figure 4.7b), a positive

slope was obtained corresponding to a standard enthalpy change (Δ◦H) of −29.7 ± 1.3 kJ mol−1.

Since the equilibrium is reached slowly in the 15 and 5◦C experiments, we can estimate the rate

coefficient of 1-HEHP formation by fitting an exponential curve to the decaying acetaldehyde

signal and obtaining its slope at early reaction times where there is no reverse reaction occurring

and the initial concentrations of acetaldehyde and H2O2 are known. Using this method, the second-

order rate constants of 1-HEHP formation were determined to be 0.012 ± 0.002 and 0.0045 ±

0.0005 M−1 s−1 at 15 and 5 ◦C, respectively. The kinetics at 25 ◦C were too fast to be estimated. We

note that the pH of the solution is not controlled in our experiment. Even though the equilibrium

134

is independent of the solution pH, both the formation and decomposition rates of α-HHP have been

reported to be pH dependent (Zhou and Lee, 1992).

Figure 4.7: Typical acetaldehyde time profiles at 5, 15 and 25 ˚C are shown in (a). The ratios of signal at a given time

to the initial signal are shown. H2O2 (13.3 mM) was injected to the 10 mM acetaldehyde solutions at time (i). The

dashed lines show the signal levels at equilibrium. The van’t Hoff diagram for 1-hydroxyethyl hydroperoxide (1-

HEHP) formation from acetaldehyde is shown in (b). The dashed lines connects +1 σ and -1 σ from the average

ln(Kapp) determined at the three temperatures.

Table 4.3: Temperature dependence of the apparent equilibrium constant (Kapp) of 1-hydroxyethyl hydroperoxide (1-

HEHP) formation from acetaldehyde.

Temperature (˚C) Kapp (M-1) # Replicates

25 132 ± 15 12

15 206 ± 40 6

5 311 ± 38 8

135

4.3.5 Effects of Inorganic Salt Addition

The results of the inorganic salt addition experiments are summarized in Table 4.4. We observed

that the addition of AS and SS caused a small increase in Khyd and a small decrease in Kapp for both

acetaldehyde and glycolaldehyde. To assess whether the differences are statistically significant,

one-tail t tests were performed to make comparisons between the average Khyd and Kapp values with

and without salt addition, and the p values from the t tests are listed in Table 4.4. P values that are

statistically significant at the 95% confidence level (i.e. p < 0.05) are indicated with an * label in

Table 4.4. All the equilibrium constants for glycolaldehyde and the Khyd of acetaldehyde with AS

addition have been determined to be statistically significant, whereas the other three values point

in the same direction but with less statistical significance.

Table 4.4: Effects of inorganic salt addition on the hydration equilibrium constant (Khyd) and the apparent α-HHP

formation equilibrium constant (Kapp).

Acetaldehyde Glycolaldehyde

Experiment Khyd and Kapp (M-1) # Replicates p-value Khyd and Kapp (M-1) # Replicates p-value

No Salt

Khyd 1.43 ± 0.04 15 - Khyd 16.0 ± 1.3 16 -

Kapp 94.8 ± 12.5 11 - Kapp 43.3 ± 3.9 12 -

1M (NH4)2SO4

Khyd 1.48 ± 0.07 4 0.11 Khyd 17.8 ± 0.3 3 *4.3 × 10-5

Kapp 81.3 ± 12.7 3 *4.0 × 10-3 Kapp 35.6 ± 2.4 3 *9.7 × 10-5

1M Na2SO4

Khyd 1.58 ± 0.04 3 0.10 Khyd 18.5 ± 0.5 3 *3.8 × 10-3

Kapp 82.3 ± 10.0 3 0.072 Kapp 30.8 ± 2.4 3 *4.8 × 10-4

*Statistically significant at the 95% confidence level (p-value < 0.05).

These observations qualitatively agree with Yu et al. (2011), who observed that addition of SS

shifted the hydration equilibrium of glyoxal to the dihydrated form of the monomer. The

enhancement of Khyd and the suppression of Kapp by SS and AS observed in the current study is

likely arising from similar effects at the molecular level, especially those associated with SO42-.

The current observation implies that the inorganic effects may affect aqueous-phase equilibria of

136

aldehydes in general. Yu et al. (2011) suggested that this effect might be more pronounced for

aldehydic functional groups adjacent to an electron-withdrawing group (e.g. glyoxal).

Glycolaldehyde has an additional electron-withdrawing hydroxyl group compared to

acetaldehyde, which may explain why the inorganic salt effect appears to be larger for

glycolaldehyde.

4.4 Atmospheric Implications

With the first thorough assessment of the equilibrium constants for α-HHP formation, we can

make initial assessments for the likely atmospheric significance for these compounds.

4.4.1 Equilibrium concentrations of α-HHPs in cloud water and aerosol liquid water

The amount of α-HHP formation via the carbonyl pathway in atmospheric aqueous phases is

directly dependent on the abundance of the different reactants. Cloud/fog water and ALW are

commonly considered as two qualitatively different reaction media (Volkamer et al., 2009; Ervens

and Volkamer, 2010; Lim et al., 2010) due to orders of magnitude differences in their liquid water

content (LWC), surface-to-volume ratio, and aqueous-phase reactant concentrations. The

aldehyde species studied here span a wide range of water solubility. Specifically, the aqueous-

phase concentrations of volatile species such as acetaldehyde, propionaldehyde, and methacrolein,

whose KH values are typically below 20 M atm−1 (Zhou and Mopper, 1990; Allen et al., 1998), are

expected to be low. However, aqueous-phase concentrations of highly water-soluble aldehydes,

such as glycolaldehyde, methylglyoxal, and glyoxal can be substantial. In particular, the

concentration of glyoxal can be up to hundreds of µM in polluted fog water (Carlton et al., 2007;

Tan et al., 2009) and has been proposed to be present up to the molar level in ALW (Volkamer et

al., 2009). Furthermore, there are also studies suggesting that H2O2 concentration in ALW can also

be unexpectedly high. Based on filter extracts of ambient aerosol and model calculations,

Arellanes et al. (2006) suspected that H2O2 concentration in ALW might be up to 100 mM,

although there is some possibility that the H2O2 that is detected has arisen from decomposition

from other species or been formed post collection in such off-line analyses. The concentration of

H2O2 in cloud water usually does not exceed 100 µM (Sakugawa et al., 1990).

137

Figure 4.8: Simulation of the equilibrium concentration of α-hydroxyhydroperoxide ([α-HHP]eq) arising from various

equilibrium concentrations of H2O2 ([H2O2]eq) and total aldehyde ([Total Aldehyde]eq). The concentrations are all

presented in log scale. Conditions relevant to cloud water and aerosol water are also indicated. This simulation

considers α-HHP formation via only the Carbonyl Pathway, with an average equilibrium constant of 100 M-1.

Assuming an average Kapp of 100 M−1, which is approximately the middle point of the measured

Kapp values from the current study, we calculated the concentrations of α-HHPs that would be

present with various equilibrium concentrations of H2O2 and total aldehyde (Figure 4.8). Note that

the effect of inorganic salts is not considered in this calculation but our studies suggest that these

effects are likely to be minor relative to the uncertainties in the assumed reactant concentrations.

The simulation indicates that α-HHP formation in cloud water is unlikely to be significant, with

its concentration not exceeding 10 µM even with the highest combination of reactant

concentrations. In ALW, however, α-HHP concentrations may be comparable to that of H2O2.

When the equilibrium concentrations of H2O2 and aldehydes reach 10 mM and 100 mM, their

respective upper limits in ALW, 100 mM of α-HHPs may be formed.

-6

-5

-4

-3

-2

log

( [H

2O

2] e

q (

M)

)

-6 -5 -4 -3 -2 -1

log( [Total Aldehyde]eq (M) )

Cloud Water Relevant Conditions

Aerosol Liquid Water Relevant Conditions

-10 -8 -6 -4 -2

log( [a-HHP]eq (M) )

138

Table 4.5: Conditions assumed in the atmospheric partitioning simulation of 1 ppb of aldehydes or H2O2.

Cloud Water Aerosol Liquid Water (ALW)

Temperature 25 C˚ 25 C˚

Atmospheric

Pressure 1 atm 1 atm

Liquid Water

Content (LWC) 1 g m-3 1 ug m-3

Aqueous-phase

H2O2 100 uM 10 mM

Aqueous-phase total

Aldehyde 100 uM 100 mM

4.4.2 Impact of α-HHP formation on the atmospheric partitioning of aldehydes and H2O2

The water solubility of α-HHP can be very high. The KH has only been reported for one α-HHP,

i.e. that from formaldehyde (HMP): 5 × 105 M atm−1 (Zhou and Lee, 1992) and 1.67 × 106 M atm−1

(O’Sullivan et al., 1996). These values are two orders of magnitude larger than that of

formaldehyde and one order of magnitude larger than that of H2O2. This implies that the formation

of α-HHP in the aqueous phase will enhance the KHeff of aldehydes and/or H2O2:

KHeff,Ald = KH,Ald(1 + Kapp[H2O2]aq) (4.6)

KHeff,H2O2= KH,H2O2

(1 + Kapp[Total Aldehyde]aq) (4.7)

Note that the KH values for aldehydes are the effective Henry’s law constant of these aldehydes

over pure water (i.e. they incorporate the hydration reaction of these aldehydes in water). The KHeff

and KH values used here should be considered as Henry’s law constants with and without α-HHP

formation, respectively. As shown in Eqn. 4.6 and Eqn. 4.7, the enhancement of KHeff compared to

KH depends on the value of Kapp and the amount of H2O2 or total aldehyde existing in the aqueous

phase.

We simulated the partitioning of an initial mixing ratio of 1ppb gas-phase aldehyde or H2O2 that

is exposed to typical cloud water or ALW conditions, both with and without α-HHP formation

(see Table 4.5). In particular, in the case of the aldehydes, we assume a fixed concentration of

139

H2O2 in solution (as specified in Table 4.5), and in the case of H2O2, we assume a fixed

concentration of dissolved total aldehydic functional group. The LWC is orders of magnitude

higher in the cloud water scenario than with ALW, i.e. 1 g m−3 vs. 1µg m−3. By contrast, the

equilibrium concentrations of total aldehyde and H2O2 are assumed to be much higher in the ALW

case. The purpose of this simple simulation is to assess how the enhancement of KHeff arising from

α-HHP formation leads to an associated alteration in the gas-aqueous phase partitioning of H2O2

and aldehydes based only on the thermodynamic equilibria of Henry’s law partitioning and α-HHP

formation. Kinetic issues, such as formation rate constants and mass transfer rates, are not

addressed, and we assume the α-HHPs are involatile. We again stress that the chemical

concentrations in ALW are highly uncertain. The assumed concentrations here (i.e. 10 mM for

H2O2 and 100 mM for total aldehyde) can be considered as their respective upper limits, and these

calculations should be viewed as a simple modelling exercise to highlight potential atmospheric

importance only. The simulation was performed for formaldehyde, acetaldehyde and H2O2, and

the results are shown in Table 4.6.

Without α-HHP formation, the majority of formaldehyde and acetaldehyde exists in the gas phase

under both scenarios, leaving their gas-phase mixing ratio essentially unaffected at 1ppb. More

than half of the H2O2 population will dissolve into the aqueous phase under the cloud water

scenario due to its relatively high KH, but the majority stays in the gas phase under the ALW

scenario due to the small LWC. The measured Kapp values for formaldehyde and acetaldehyde from

the current work are used for the simulation of α-HHP formation. For the case of H2O2 simulation,

an average Kapp of 100 M−1 was assumed.

The first conclusion from the simulation is that, in the ALW scenario, KHeff values of H2O2 are

enhanced by up to an order of magnitude relative to the KH values when α-HHP formation occurs,

while the enhancement in the cloud water scenario was minor. However, even with such large

enhancement in the KHeff values, the gas-phase mixing ratio of aldehydes and H2O2 are essentially

unchanged from the case without α-HHP formation because of the low LWC. The KHeff values for

formaldehyde and acetaldehyde were also enhanced by over a factor of two in ALW when α-HHP

formation occurs.

140

The second conclusion arises from the resulting α-HHP concentration in the aqueous phase.

Particularly in the H2O2 simulation, by assuming a total aldehyde concentration of 100 mM at

equilibrium in the ALW scenario, approximately 0.7 mM of α-HHP forms in ALW. We raise the

possibility that this high concentration of α-HHP may partially explain the surprisingly high

concentrations of H2O2 previously observed from ambient aerosol (Hasson et al., 2003; Arellanes

et al., 2006). As suggested by these researchers, because of the dilution associated with ambient

aerosol extraction, α-HHPs should completely decompose to H2O2 upon analysis, contributing to

its high concentrations observed from the extract. Indeed, for this simulation, the concentration of

the α-HHP present in solution is roughly an order of magnitude larger than the concentration of

H2O2 in solution. The α-HHP concentrations in the formaldehyde and acetaldehyde simulations

were all enhanced, but not nearly as much as the H2O2 simulation case.

Of course, these assumptions are highly dependent on the assumed concentration of aldehydic

functional groups in ALW, and that they all participate in α-HHP formation with the assumed Kapp.

The degree to which such groups are present in ALW is poorly characterized; however it would

be expected that fresh SOA, for example that formed by ozonolysis, will have these species

present.

4.4.3 Other Atmospheric Implications

As mentioned previously, α-HHP can also form via the hydrolysis of SCI, i.e. the Criegee pathway.

If this reaction occurs in cloud water, the resultant α-HHP would most likely decompose to H2O2

and a corresponding carbonyl compound. However, if a hydrolysis reaction of SCI occurs in ALW,

which is generally more concentrated than cloud water, the resulting α-HHP may not fully

decompose given the α-HHP equilibria studied in the current work. If the α-HHP does decompose,

the H2O2 generated from the decomposition of α-HHP may meet another aldehydic species with

higher concentration (e.g. glyoxal) to form a different α-HHP.

As α-HHP concentration builds up in ALW, α-HHP themselves can act as nucleophiles and form

peroxyhemiacetals by reacting with aldehydic functional groups (see pathway 3 in Figure 4.1), as

in the case of BHMP formation from HMP and formaldehyde (Sect. 4.3.3.1). This reaction of α-

HHP is a specific mechanism of peroxyhemiacetal formation initially proposed by Ziemann and

co-workers (Tobias and Ziemann, 2000; Docherty et al., 2005) and later confirmed by several

141

recent laboratory studies (Hall and Johnston, 2012; Yee et al., 2012). The current study is an

indication that H2O2 can undergo the analogous reaction.

Table 4.6: Results of the atmospheric partitioning simulation.

Formaldehyde Acetaldehyde H2O2

Cloud Water ALW Cloud Water ALW Cloud Water ALW

Without

α-HHP

Formation

a KH (M atm

-1) 3.0 × 10

3 17 7.10 × 10

4

Gas-phase

mixing ratio (ppb) 0.932 1.000 1.000 1.000 0.366 1.000

Fraction in

aqueous phase 0.068 7.33 × 10

-8 4.15× 10

-4 4.15 × 10

-10 0.634 1.74 × 10

-6

Kapp

(M-1

) 164 b 113

c 100

With α-HHP

Formation

KHeff (M atm-1

) 3.05 × 103 7.92 × 10

3 17 36 7.17 × 10

4 7.81× 10

5

Gas-phase

mixing ratio (ppb) 0.931 1.000 1.000 1.000 0.363 1.000

Fraction in

aqueous phase 6.93 × 10

-2 1.94 × 10

-7 4.20 × 10

-4 8.86 × 10

-10 0.637 1.91 × 10

-5

Aqueous-phase total

α-HHP (M) 4.27 × 10

-8 4.92 × 10

-6 1.92 × 10

-10 1.92 × 10

-8 9.43 × 10

-9 7.1 × 10

-4

a KH values for formaldehyde and acetaldehyde represent their effective Henry's law constants in pure water, not

having been affected by α-HHP formation. References: formaldehyde (Betterton and Hoffmann (1988)); acetaldehyde

(Zhou and Mopper (1990)); H2O2 (Martin and Damschen (1981)).

b Value taken from the current work as the average of the NMR results and the PTR-MS results.

c Value assumed as the average Kapp for α-HHP from all the aldehyde species.

Formation of such hydroxyl and hydroperoxyl functional groups reduces the vapour pressure of

an organic compound substantially (Kroll and Seinfeld, 2008) and increases its solubility. It is

possible that peroxyhemiacetals and α-HHPs can stay in the particle phase even after water

evaporation and can thus be a pathway by which relatively volatile aldehydes are involved in SOA

formation. Recently, Liu et al. (2012) observed that addition of H2O2 to the water extract of

isoprene SOA caused significant increases in its degree of oxygenation and enhancement of its

hygroscopicity. It is likely that the α-HHP and peroxyhemiacetals contributed to such physico-

142

chemical changes of the SOA water extract. In fact, decay of carbonyls and significant formation

of 1-HEHP were observed in their study.

The α-HHPs may also be photolysed by actinic radiation, leading to the cleavage of the peroxide

(O–O) bond and the regeneration of an OH radical (Monod et al., 2007; Roehl et al., 2007;

Kamboures et al., 2010). It needs to be determined whether this process occurs more readily with

α-HHPs or with their precursor, H2O2. As well, the reactivity of α-HHPs with the OH radical is

likely to be high. Our previous study (Zhao et al., 2012) suggested that a major fraction of formic

acid observed during glyoxal photooxidation proceeded via an α-HHP intermediate.

Finally, we note that α-HHPs will likely decompose if aerosol is exposed to the fluid lining the

lung, providing a source of reactive oxygen species such as H2O2 to the body. In particular, Hasson

and Paulson (2003) indicate that the minimum H2O2 concentration to cause damage to alveolar

cell is likely to be at the order of 0.1 to 1 mM in ALW. Our simulations above suggest that the α-

HHP concentration have the potential to be at or above this minimum level.

4.5 Conclusions

We have investigated the thermodynamics of aqueous-phase formation of α-

hydroxyhydroperoxides (α-HHP) arising from H2O2 reacting with a suite of atmospherically

relevant carbonyl compounds. We find that formation of α-HHP was significant from many small,

atmospherically relevant aldehydes, but not from methacrolein and ketones. We have also

performed preliminary simulations to demonstrate that α-HHP formation will likely be of minor

importance in cloud water but is more likely to be of importance in aerosol liquid water (ALW)

where the concentrations of H2O2 and aldehydes are higher. In ALW, α-HHP may significantly

enhance the effective Henry’s Law constants of aldehydes and H2O2, leading to significant

concentrations of α-HHP in solution but probably not affecting the gas-phase levels of these

chemicals. The influence of α-HHP formation at lower temperatures, however, may be more

significant due to the enhancement of their formation equilibrium constants. We have also found

that α-HHPs can further act as nucleophiles to form peroxyhemiacetals. In general, this chemistry

is likely to lead to higher concentrations of organic peroxides than expected in ALW. The fate of

143

this class of compounds and their influence in aqueous-phase reaction mechanisms should be

further investigated.

Acknowledgement

The authors thank NSERC and QEII-GSST for financial support.

Supplementary Information

Supplementary information for this chapter is given in Appendix B.

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Chapter 5

Photochemical Processing of Aqueous Atmospheric Brown Carbon

As published in Atmos. Chem. Phys. Discuss. 15: 2957-2996, DOI:10.5194/acpd-15-2957-2015.

Distributed under the Creative Commons Attribution 3.0 License.

152

Abstract

Atmospheric Brown Carbon (BrC) is a collective term for light absorbing organic compounds in

the atmosphere. While the identification of BrC and its formation mechanisms is currently a central

effort in the community, little is known about the atmospheric removal processes of aerosol BrC.

As a result, we report a series of laboratory studies of photochemical processing of BrC in the

aqueous phase, by direct photolysis and OH oxidation. Solutions of ammonium sulfate mixed with

glyoxal (GLYAS) or methylglyoxal (MGAS) are used as surrogates for a class of secondary BrC

mediated by imine intermediates. Three nitrophenol species, namely 4-nitrophenol, 5-

nitroguaiacol and 4-nitrocatechol, were investigated as a class of water soluble BrC originating

from biomass burning. Photochemical processing induced significant changes in the absorptive

properties of BrC. The Imine-mediated BrC solutions exhibited rapid photo-bleaching with both

direct photolysis and OH oxidation, with atmospheric half-lives of minutes to a few hours. The

nitrophenol species exhibited photo-enhancement in the visible range during direct photolysis and

the onset of OH oxidation, but rapid photo-bleaching was induced by further OH exposure on an

atmospheric timescale of an hour or less. To illustrate atmospheric relevance of this work, we also

performed direct photolysis experiments on water soluble organic carbon extracted from biofuel

combustion samples and observed rapid changes in optical properties of these samples as well.

Overall, these experiments indicate that atmospheric models need to incorporate representations

of atmospheric processing of BrC species to accurately model their radiative impacts.

5.1 Introduction

There is increasing awareness of the importance of light absorbing organic compounds in the

atmosphere (Kirchstetter et al. 2004, Chen and Bond 2010, Lack et al. 2012, Bahadur et al. 2012).

Highly variable in sources and identity, this class of poorly characterized organic compounds has

been collectively termed Atmospheric Brown Carbon (BrC) (Andreae and Gelencser 2006). BrC

significantly alters the traditional view that organic carbon interacts with solar radiation via only

scattering (Chung and Seinfeld 2002). In the visible range of solar radiation, BrC absorption can

affect the direct radiative effect of organic carbon (Feng et al. 2013, Lin et al. 2014). In particular,

Feng et al. (2013) have shown that defining a fraction of organic aerosol as strongly light-absorbing

BrC in a global chemical transport model can shift the direct radiative effect of organic carbon

153

from net cooling to net warming. Meanwhile in the near UV range, BrC absorption may affect the

flux of short-wavelength radiation that is crucial in driving atmospheric photochemistry (Jacobson

1999). Motivated by such atmospheric impacts, the characterization of the sources, molecular

identity and processing of BrC is a central effort in the aerosol chemistry community.

There are two major types of BrC widely studied. The first arises from primary organic compounds

emitted during biomass burning (BB) (Andreae and Gelencser 2006, Alexander et al. 2008, Chen

and Bond 2010, Lack et al. 2012, Kirchstetter and Thatcher 2012, Saleh et al. 2014). The chemical

composition of BB organic aerosol is highly complex, which varies significantly with source fuels,

burning conditions and atmospheric age of the particles (Chen and Bond 2010, Cubison et al. 2011,

Ortega et al. 2013). Such complexity significantly hinders the separation, analyses, and molecular

identification of BB BrC. BB BrC is at times considered to belong to Humic Like Substances

(HULIS) (Hoffer et al. 2004, Graber and Rudich 2006) and more recently a class of compounds

categorized as extremely low volatility organic compounds (Saleh et al. 2014).

The second BrC source involves secondary chemistry occurring in atmospheric aqueous phases

(e.g. cloudwater and aerosol liquid water) between aldehydes and nitrogen containing

nucleophiles, including ammonia, amino acids and amines (De Haan et al. 2009, Shapiro et al.

2009, Sareen et al. 2010, De Haan et al. 2011, Yu et al. 2011, Zarzana et al. 2012, Sedehi et al.

2013, Powelson et al. 2013). Since the formation mechanism of this type of BrC involves an imine

or a Schiff’s base intermediate, this class of BrC is herein referred as “Imine BrC”. Although imine

intermediates do not absorb at the actinic range, they undergo subsequent reactions to form

nitrogen-containing organic chromophores (Lee et al. 2013, Kampf et al. 2012, Yu et al. 2011). It

is generally believed that formation of individual chromophores with very low concentrations

leads to the color (Nguyen et al. 2013). Imine BrC typically takes days to form in the bulk

laboratory solution (Lee et al. 2013). However, studies have also shown that droplet evaporation

may significantly accelerate the rate of such reactions, giving rise to rapid formation of BrC (De

Haan et al. 2011, Zarzana et al. 2012, Lee et al. 2013, Galloway et al. 2014). Finally, we note that

a recent study has also suggested that charge transfer complexes between different functional

groups may be responsible for absorption in the visible range (Phillips and Smith 2014). We did

not perform experiments targeted to this potential third class of BrC species.

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Studies from the past decade (Blando and Turpin 2000, Ervens et al. 2011) have indicated

atmospheric aqueous phases (e.g. cloudwater and aerosol liquid water) as important reaction

media, where organic compounds can be processed, leading to formation and further aging of

secondary organic aerosol (SOA). Imine BrC, forming in the aqueous phase, can undergo

subsequent photochemical processing. A previous study has observed rapid photolysis of

components in the mixture of methylglyoxal and ammonium sulfate, implying rapid photolysis of

Imine BrC (Sareen et al. 2013). More recently, Lee et al. (2014b) investigated aqueous-phase

processing of several classes of BrC and observed rapid decay of color (photo-bleaching). To date,

there is no systematic investigation of the effect of OH oxidation on Imine BrC. BB BrC, on the

other hand, can also be subject to aqueous-phase photochemical processing, given that BB

particulate matter can be hygroscopic (Petters and Kreidenweis 2007, Petters et al. 2009) and

contains a significant fraction of water soluble organic carbon (Iinuma et al. 2007, Saarikoski et

al. 2008, Chen and Bond 2010). While the majority of BB BrC remains unidentified, nitrophenols

present a useful class of model compounds to investigate aqueous-phase processing of BB BrC.

They have been frequently identified in BB plumes (Vione et al. 2009, Einschlag et al. 2009) and

have been employed as molecular tracers for BB (Iinuma et al. 2010, Kitanovski et al. 2012, Mohr

et al. 2013). Certain nitrophenols exhibit relatively high Henry’s law constants (Schwarzenbach et

al. 1988) and have been observed in cloudwater samples (Luttke and Levsen 1997, Luttke et al.

1999, Harrison et al. 2005). In particular, Desyaterik et al. (2013) have determined BrC from

cloudwater affected by BB and have identified multiple species of nitrophenols that contribute

towards the total absorption of the cloudwater sample. Hence, nitrophenols represent an important

subclass of BB water soluble organic carbon (WSOC) that may undergo aqueous-phase

processing. Previous studies have investigated aqueous phase UV photolysis (Chen et al. 2005,

Zhao et al. 2010), OH oxidation (Einschlag et al. 2003, Vione et al. 2009, Einschlag et al. 2009),

as well as heterogeneous oxidation (Knopf et al. 2011, Slade and Knopf 2014) of nitrophenols, but

a clear connection to their optical properties has not been made.

In this study, we systematically investigate how atmospheric photochemical processing

mechanisms affect Imine BrC and nitrophenols (as surrogates of BB BrC) in the aqueous phase,

focusing on changes in their absorptive optical properties. The dual objectives are 1) to quantify

the rates of direct photo-bleaching and/or photo-enhancement under realistic radiation condition,

and 2) to evaluate the atmospheric importance of BrC oxidative processing, with a particular focus

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on OH oxidation. We perform these experiments quantitatively under known light and OH

exposures, so as to establish which processing mechanism is likely to dominate in the atmosphere.

To tie our laboratory experiments to ambient conditions, we also performed direct photolysis

experiments on the WSOC extracted from biofuel combustion particles.

5.2 Methods

5.2.1 Preparation of BrC Solutions

The experimental procedures for Imine BrC and nitrophenols are illustrated in Figure 5.1.

Solutions of ammonium sulfate mixed with glyoxal (GLYAS) or methylglyoxal (MGAS) were

chosen as laboratory surrogates to represent Imine BrC. Stock solutions (200 mL in volume) were

made by mixing ammonium sulfate (1.5 M, Sigma Aldrich) with either 0.5 M of glyoxal (Sigma

Aldrich, 30 % in water) or 0.2 M of methylglyoxal (Sigma Aldrich, 40 % in water) in 250 mL

glass jars. All the solutions were prepared using deionized water (18 mΩ-cm) with total organic

carbon less than 1 parts per billion (ppb). The stock solutions were sealed and placed in the dark

under room temperature for 2 to 3 months. During this time, the color of the solutions turned dark

yellow and eventually dark brown, consistent with previous studies (Shapiro et al. 2009, Sareen et

al. 2010, Lee et al. 2013). Although 2 to 3 months is much longer than typical atmospheric aerosol

lifetimes, our previous work has shown that the absorption spectra of Imine BrC obtained this way

closely resembled those obtained from droplet evaporation occurring on the timescale of seconds

or less (Lee et al. 2013). The experimental solutions were created by diluting the concentrated

stock solutions, typically by a factor of 200, to concentrations that optimize the UV-Vis detection

at 400 nm (see next section).

Three nitrophenol compounds (4-nitrophenol (4NP), 5-nitroguaiacol (5NG) and 4-nitrocatechol

(4NC)) were chosen to represent primary BB BrC (structures shown in Figure 5.2) and are

investigated individually. 4NP and 4NC have been detected from BB affected cloudwater samples

(Desyaterik et al. 2013) while 5NG has been previously used in the laboratory as a model

compound for BB organic matter (Knopf et al. 2011). Commercial standards of these compounds

were purchased from Sigma Aldrich and were used without further purification. Individual stock

solutions (1 mM) were created every few days, and the experimental solutions were made by

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diluting the stock solution to 4 to 15 uM depending on the nitrophenol species and the type of

experiment. This range of concentration matches that of nitrophenols detected in cloudwater

(Desyaterik et al. 2013).

Figure 5.1: Experimental procedures.

5.2.2 Direct Photolysis and OH Oxidation Experiments

Direct photolysis and OH oxidation experiments were conducted separately. Direct photolysis

experiments were performed with a Suntest CPS photo-simulator (Atlas) equipped with a Xe lamp.

The BrC solution (100 mL) contained in a glass bottle was placed inside the simulator for

illumination. Chemical actinometry using 2-nitrobenzaldehyde (Galbavy et al. 2010) was

performed to measure the effective photon flux which was determined to be similar to actinic flux

at the Earth’s surface with 0 ˚C zenith angle. The method of chemical actinometry and the

determined photon flux from the simulator are included in Appendix C, Section C1. Aliquots of

the experimental solution were taken at different illumination times for offline absorption

measurements conducted by a liquid waveguide capillary UV-Vis spectrometer (World Precision

Instruments), equipped with a deuterium tungsten halogen light source (DT-Mini-2, Ocean Optics)

and a temperature controlled UV-Vis spectrometer (USB2000+, Ocean Optic). The strength of this

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instrument lies in its long effective optical length (50 cm in this work), resulting in its superior

detection sensitivity. The spectrometer simultaneously records absorption from 230 to 850 nm,

making monitoring at multiple wavelengths possible. We confirmed that the concentrations of the

experimental solutions were in the linear range of the spectrometer used.

Experiments for OH oxidation were conducted in a different setup. Hydrogen peroxide (H2O2,

TraceSELECT® 30% purchased from Sigma Aldrich) was added to each solution as a photolytic

source of OH radical upon irradiation with a 254 nm mercury lamp (UVP, an ozone-free version

constructed to remove the 185 nm line) inserted inside the solution. The BrC solutions were

prepared in the same manner but in a larger volume (1 L). The concentration of H2O2 added to the

BrC solutions was typically 5 mM unless otherwise stated. H2O2 itself exhibited UV absorption

up to 300 nm, but did not affect BrC absorption at longer wavelengths. Dark control experiments

were also performed to confirm that H2O2 did not react with BrC to change its optical properties.

Aliquots of offline samples were taken at different illumination times and were measured by the

liquid waveguide capillary UV-Vis spectrometer as mentioned above.

It is crucial to measure the steady state concentration of OH radicals ([OH]ss) in the OH oxidation

experiments in order to infer sound environmental implications. An aerosol chemical ionization

mass spectrometer (Aerosol CIMS) was employed for this purpose. The experimental setup is

similar to that in one of our previous studies (Zhao et al. 2012). Briefly, the experimental solution

is constantly atomized with a TSI constant output atomizer (model 3076). The aerosol flow is

introduced through a heated metal line (100 ˚C), where organic compounds volatilize to the gas

phase and are detected by a quadruple CIMS equipped with iodide water cluster reagent ion

(I(H2O)n-). The I(H2O)n

- reagent ion detects oxygenated organic compounds by forming iodide ion

clusters (Aljawhary et al. 2013, Lee et al. 2014a, Zhao et al. 2014). The [OH]ss was estimated by

tracking the pseudo 1st order decay of a reference compound with known OH reactivity. For the

Imine BrC, unreacted glyoxal or methylglyoxal in the solutions were used as the tracer compounds

because their mono-hydrates are detectable by the I(H2O)n- reagent ion (Zhao et al. 2012). The OH

oxidation rate constants of glyoxal and methylglyoxal used in this study are 1.1 × 109 M-1s-1 (Tan

et al. 2009) and 5.3 × 108 M-1s-1 (Monod et al. 2005), respectively. For the nitrophenols, as the

iodide reagent ion does not detect nitrophenol species, 1 mM of meso-erythritol (Sigma Aldrich)

was added to the solution as the reference compound. The choice of erythritol is based on the fact

that: 1) it does not absorb light in the actinic wavelength, 2) it is not an acid and does not affect

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the solution pH, and 3) it reacts with OH rapidly, with a second order rate constant of 1.9 × 109 M-

1s-1 (Hoffmann et al. 2009).

5.2.3 Direct Photolysis of WSOC from Biofuel Combustion

The biofuel combustion samples were collected in Henan Province, China (Li et al. 2007, Li et al.

2009). Agricultural residues, typically used as biofuels in the local area, were burned in an

improved stove commonly used in the area. A detailed description of particle collection and the

physical properties of the generated particles are provided in Li et al. (2007). Briefly, particles

were withdrawn from the stove, and the PM2.5 fraction was collected on quartz filters after

dilution. The quartz filters were baked under 450 ˚C before collection, and the samples were stored

frozen after collection. Organic carbon (OC) and elemental carbon contents of each filter sample

were measured following a method originally developed at Environment Canada’s laboratory in

Toronto for measuring δ13C of OC/EC (Huang et al., 2006) and later improved by Chan et al. ,

2010 to be used as the standard OC/EC measurements in the aerosol baseline measurements in

Canada. In the current work, we investigated the WSOC from two filter samples, collected from

burning of kaoliang stalks and cotton stalks, respectively. A quarter of the filter was extracted in

10 mL of deionized water by constant shaking for 30 min. The extracts were used as the experiment

solution after filtration with a 0.2 µm syringe filter. We extracted the same filter a second time and

found that the absorption in the second extract was less than 10 % of the first extract. However, it

is difficult to estimate the extraction efficiency of total organic carbon. The filtered extract was

illuminated with the same solar simulator, and its absorption was monitored with the same

waveguide capillary spectrometer mentioned in Section 5.2.2. Oxidation by OH radicals was not

performed for these samples due to limited amount of sample volume.

5.3 Results and Discussion

5.3.1 Light Absorption of BrC

Absorption spectra of the BrC solutions are displayed in Figure 5.2a. The concentrations of the

solutions were chosen to display their full absorption spectra up to 480 nm. The absorption spectra

of all of these species stretch into the visible range of radiation, giving rise to brown to light yellow

color to the solutions. Absorption spectra of the two WSOC extracts from biofuel combustion

samples are shown in Figure 5.2b. Absorption with strong wavelength dependence was observed,

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with Angstrom absorption coefficients (290 to 480 nm) of 6.0 and 5.8 for the kaoliang stalk and

cotton stalk samples, respectively.

Figure 5.2: Absorption spectra of BrC investigated in this study (a) and WSOC from the biofuel combustion samples

(b). The y-axis in (a) is in arbitrary units to keep the absorbance of all the solutions on scale.

We note that the absorption spectra of the individual BrC species do not resemble those of the

biofuel sample extracts, as such ambient samples likely contain a large number of BrC compounds

with various absorptivity. Investigation of the selected Imine BrC and nitrophenol species in this

study is intended to provide fundamental information for processing of individual BrC species.

To provide more quantitative values, we also obtained the wavelength dependent mass absorption

coefficient (MAC) for the Imine BrC and biofuel combustion samples. The MAC of the Imine BrC

solutions was calculated based on its total organic carbon content measured by a Shimadzu TOC-

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ICPH Total Organic Carbon Analyzer. The MAC of the biofuel combustion samples was

calculated based on its organic carbon contents measured in the filter samples. For nitrophenols,

we obtained their absorption coefficient and molar absorptivity instead of MAC because they are

single compounds. The detailed methods and complete results are shown in Appendix C, Section

C2.

5.3.2 Imine BrC

5.3.2.1 Direct Photolysis of Imine BrC

Both GLYAS and MGAS solutions exhibited rapid photo-bleaching upon illumination by

simulated sunlight. Figure 5.3a shows the spectral change of one MGAS solution as an example,

with the illumination time color-coded. Absorbance over the entire spectral range exhibited

uniform decay during two hours of illumination. In Figure 5.3b, we show the time profiles of

absorbance at 400 nm normalized to its initial value at t=0 for both the GLYAS and MGAS

solutions. The wavelength of 400 nm was chosen because the concentrations of the Imine BrC

solutions were optimized for the detection at this wavelength. The inset displays the 1st order plots

for the decay, alone with the fitted linear lines forced through the origin. The non-linear plots

indicate non-1st order behavior, likely due to the presence of multiple chromophores that exhibit

different degrees of photo-lability.

Aregahegn et al. (2013) proposed that photosensitized reactions take place in the GLYAS solution,

initialized by compounds such as imidazole and imidazole-carboxaldehyde. We examined the

presence of this type of reaction by varying the initial concentration of the Imine BrC. However,

the concentration of Imine BrC did not affect its photolysis rate constant (Appendix C, Section

C3). This indicates that photosensitized reactions either did not take place in our reaction system,

or were not indicated by the color change.

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Figure 5.3: Spectral change of the MGAS solution during a direct photolysis experiment (a) and the absorbance

change at 400 nm as a function of illumination time (b). The inset in (b) shows the 1st order plot of the decay, and the

lines are linear least square plots forced through the origin. The shaded area represent the range obtained from 3

replicates.

5.3.2.2 OH Oxidation of Imine BrC

Rapid photo-bleaching was observed also during the OH oxidation experiments. Figure 5.4a shows

the evolution of absorbance at 400 nm during four experiments, normalized to the values at the

beginning of illumination. The dashed lines are H2O2 control experiments, where the absorbance

at 400 nm for both GLYAS and MGAS exhibited decay due to direct photolysis by the 254 nm

lamp. The decay was clearly accelerated during OH oxidation experiments represented by the solid

line traces. The calculated [OH]ss values in these two experiments were 9 × 10-14 M and 1 × 10-13

M for the GLYAS and MGAS experiments, respectively.

Table 5.1: Estimated atmospheric half-life of Imine BrC arising in the glyoxal-ammonium sulfate (GLYAS) and

methylglyoxal-ammonium sulfate (MGAS) solutions.

Photolytic τ1/2

(min) kIIOH (M-1 s-1) OH τ1/2 (min)

GLYAS 90 ± 12 2.1 (± 1.1) × 1010 5

MGAS 13 ± 3 1.2 (± 0.3) × 109 98

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The decay of absorbance at 400 nm appeared largely pseudo 1st order, except for the GLYAS OH

oxidation (Figure 5.4b). Similar to the case of direct photolysis, we suspect that multiple

chromophores likely give rise to the non-1st order decay of the color. We have decided to treat the

decay in the GLYAS system as if it was pseudo 1st order, with the rates determined this way

representing the middle point between the fastest and slowest decay rate.

Assuming the difference between the H2O2 control and the OH oxidation experiments is due to

OH oxidation, a pseudo 1st order OH oxidation rate constant (kIOH) can be obtained by taking the

difference between the observed pseudo 1st order decay of absorbance in the H2O2 control (kIctl)

and the OH oxidation experiments (kIoxi), as shown by Eqn 5.1. The second order OH oxidation

rate constant (kIIOH) can then be calculated from Eqn. 5.2.

kIOH = kI

oxi - kIctl (5.1)

kIIOH = kI

OH / [OH]ss (5.2)

As listed in Table 5.1, the kIIOH values for the GLYAS and the MGAS systems are determined to

be (2.1 ± 1.1) × 1010 and (1.2 ± 0.3) × 109 M-1s-1, respectively. The uncertainty represents standard

deviation from between 3 and 4 experimental replicates. We note that the kIIOH value for the

GLYAS system is essentially diffusion limited.

Figure 5.4: Time profiles of absorbance at 400 nm during OH oxidation (solid lines) and H2O2 control (dashed lines)

experiments. Results for both the GLYAS (blue traces) and the MGAS (red traces) solutions are shown. The decay

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profiles of absorbance at 400 nm normalized to the initial value at t =0 are shown in (a), while their corresponding 1st

order decay plots are shown in (b).

5.3.2.3 Atmospheric Fate of Imine BrC

We estimate the atmospheric half-life (τ1/2) of Imine BrC against direct photolysis and aqueous

phase OH oxidation based on the observed absorbance change at 400 nm (Table 5.1). The τ1/2

values were obtained by extracting the time when the signal reached half of its original value, and

the uncertainty represents the range obtained from three replicates. Since the photon flux in the

solar simulator is similar to that in the ambient atmosphere (see Appendix C, Section C1), the

experimentally determined τ1/2 values, 90 ± 12 min and 13 ± 3 min for the GLYAS and MGAS

systems, directly reflect the photolytic τ1/2 of these Imine BrC species in the ambient atmosphere.

These τ1/2 values are on the same order as those derived for another type of Imine BrC generated

from Limonene SOA and ammonia vapor (Lee et al. 2014b), implying that rapid photolysis will

be a common characteristic for this type of Imine BrC. The OH oxidation half-lives are estimated

by assuming an ambient cloudwater [OH]ss of 1 × 10-13 M (Herrmann et al. 2010). This [OH]ss,

together with the kIIOH determined in the previous section (Section 5.3.2.2), yields OH oxidation

τ1/2 of 5 min and 98 min for the GLYAS and the MGAS solutions, respectively. The rapid

bleaching implies that the daytime lifetime of Imine BrC is likely very short in the atmosphere,

leading to relatively low concentrations. Knowing that droplet evaporation can lead to rapid

formation of Imine BrC on a time scale of seconds (Lee et al. 2013), its steady state concentration

may be highest where droplet evaporation processes are occurring at night.

Although Imine BrC in the GLYAS and MGAS solutions is thought to be arising from similar

reaction mechanisms (De Haan et al. 2011, Yu et al. 2011, Sedehi et al. 2013), their major

bleaching processes are found to be different. The GLYAS solution is predominantly bleached by

OH oxidation, while the MGAS solution is by direct photolysis. The results for the MGAS solution

shows agreement with Sareen et al. (2013), where they determined direct photolysis as the

dominant sink for constituents in the MGAS solution. To our best knowledge, the current work

presents the first investigation for direct photolysis of GLYAS, as well as the OH oxidation kinetics

for both GLYAS and MGAS.

The difference in the major removal mechanisms for GLYAS and MGAS arises from the

additional methyl group on methylglyoxal as compared to glyoxal, as we propose in Figure 5.5.

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The methyl group prevents the carbonyl functionality from hydrating into its geminal diol which

does not absorb actinic radiation. On the other hand, H-abstraction from a methyl hydrogen is

expected to be slower than from the tertiary hydrogen on the geminal diol. In Figure 5.5, we use

imidazole carboxaldehyde, proposed as a major product in the GLYAS solution (Kampf et al 2012,

De Haan et al. 2011, Yu et al. 2011), as an example to demonstrate this concept.

Figure 5.5: Proposed explanation for the difference in the major bleaching processes of the GLYAS and the MGAS

solutions.

5.3.3 Nitrophenols

5.3.3.1 Direct Photolysis of Nitrophenols

The spectral change of a 4NC solution during a direct photolysis experiment is shown in Figure

5.6, color coded by illumination time, with the inset illustrating the change at different illumination

times. The change is dynamic, with a decrease of absorption between 300 and 380 nm but an

increase of absorption at 260 nm and above 400 nm. The spectral change is likely due to a

combination of 4NC decay and formation of one or more reaction products. Similar trends were

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also observed for 4NP and 5NG (Appendix C, Section C4). The most noteworthy observation for

all the nitrophenols is a photo-enhancement of absorption at wavelengths longer than 400 nm, i.e.

in the visible range. Since the photo-enhancement at 420 nm was the most significant for all the

three nitrophenols, we conducted a series of experiments to better characterize the absorbance

change at this wavelength. Formation of color at 420 nm is 1st order with respect to the precursor

nitrophenols, confirmed by altering their concentrations. The discussion below is primarily based

on the results from 4NC, while the results of 4NP and 5NG are included in Appendix C, Section

C5.

Figure 5.6: Spectral change of a 4NC solution (4 µM) during a direct photolysis experiment. The inset shows the

absorbance change compared to the initial condition.

The effect of OH radical is examined first. Previous studies have shown that nitrite ion can be

produced during UV irradiation of nitro-aromatic compounds, via photo-induced nucleophilic

substitution reactions (Nakagawa and Crosby 1974, Dubowski and Hoffmann 2000, Chen et al.

2005). Nitrite is a photolytic source of OH radical and can potentially affect our direct photolysis

experiments. We performed experiments with 1 mM of glyoxal added to the nitrophenol solution

as an OH scavenger. Glyoxal is a good scavenger because neither it nor its reaction products absorb

in the wavelength range of interest. Judging from the OH reactivity of nitrophenols (Einschlag et

al. 2003) and glyoxal (Tan et al. 2009), 1 mM of glyoxal will scavenge at least 90 % of OH radicals

in the solution. The result of a 4NC experiment with OH scavenger is shown as the cyan trace in

Figure 5.7, which does not exhibit significant difference from the experiment without the OH

scavenger (blue trace). For 4NP, the OH scavenger reduced but did not completely remove the

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color formation at 420 nm (Appendix C, Section C5). We conclude that photo-enhancement is

indeed induced by direct photolysis even without OH radicals present.

Effects of the solution pH are also examined because the light absorption of phenolic compounds

is pH dependent, with phenolate being a better absorber than phenol. Phenolate contains additional

lone-pair electrons that can participate in the conjugation system, leading to more efficient light

absorption. The absorption spectra of the three nitrophenols at various solution pH values are

shown in the Appendix C, Section C6. Light absorption of 4NP and 4NC at 420 nm increased

significantly at higher solution pH due to formation of phenolate, but 5NG did not exhibit pH

dependence. A meta-nitrophenol compound, such as 5NG, is known to be less acidic than para-

and ortho-nitrophenols (i.e. 4NP and 4NC). It is likely that the 5NG phenolate did not form in the

range of pH investigated.

The absorbance (420 nm) time profiles of 4NC at two additional solution pH (i.e. pH 4 and 3) are

displayed in Figure 5.7. The photo-enhancement is more significant at higher solution pH. This is

perhaps due to the fact that the products formed also exhibit pH dependent light absorptivity. 4NP

and 5NG exhibit unique trends of pH dependence as shown in Appendix C, Section C5.

Figure 5.7: Time profiles of 4NC absorbance at 420 nm during direct photolysis experiments. Experiments were

performed at three solution pH values. An OH scavenger experiment was also performed by adding 1 mM glyoxal to

the pH 5 solution.

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We determined the effective 1st order rate coefficient of photo-enhancement (kIdirect) for 4NC by

fitting the observed absorbance at 420 nm to a 1st order growth curve. The kIdirect values determined

for 4NC are summarized in Table 5.2. Photo-enhancement in the cases of 4NP and 5NG exhibited

stronger linearity, which made fitting to 1st order growth curve difficult. Instead of kIdirect, we report

an absorbance-based rate constant for these two compounds, and the details are provided in the

Appendix C, Section C5.

Table 5.2: Rate constants for photo-enhancement at 420 nm for 4-nitrocatechol (4NC)

kIdirect (s

-1) of 4NC

pH3 pH4 pH 5 pH 5 OH scav.

2.3 × 10-4 3.2 × 10-4 4.0 × 10-4 3.3 × 10-4

5.3.3.2 OH Oxidation of Nitrophenols

Oxidation by OH radicals induced rapid bleaching of all nitrophenols investigated, but the decay

of absorbance was not monotonous. The spectral change of 4NC during an OH oxidation

experiment is shown in Figure 5.8a while the time profile of absorbance at 420 nm is shown in

Figure 5.8b. Results for 4NP and 5NG can be found in the Appendix C, Section C7. All the

experiments were performed at pH 5 and in duplicate to confirm reproducibility. For all three

nitrophenols, the absorbance exhibited initial increase, followed by decay at longer illumination

time.

The initial color formation observed in the current study exhibits similarities with several previous

investigations of BB BrC. Gelencser et al (2003) and Chang and Thompson (2010) have observed

color formation in aqueous-phase OH oxidation of aromatic compounds. Saleh et al. (2013) have

observed light-absorbing SOA arising from BB particles photochemically aged in a chamber. More

recently, Zhong and Jang (2014) have observed a highly dynamic evolution of the optical

properties of BB particles, similar to observations from the current study. In their study, the light

absorption of BB particles in an outdoor chamber exhibited initial enhancement and subsequent

bleaching with exposure to natural sunlight. It is likely that the magnitude of photo-enhancement

and bleaching is dependent to both the BrC components and the extent of photochemical

processing. Given that nitrophenol presents only a subset of colored components in BB BrC, we

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cannot make conclusions on the general fate of BB BrC. As will be seen in Section 5.3.4, WSOC

from real BB particles indeed show complicated results, with different samples exhibiting different

trends during direct photolysis.

Figure 5.8: Spectral change of 4NC solution (10 µM) during an OH oxidation experiment (a), with the inset showing

absorbance change compared to the initial condition. The color coding represents the illumination time. The time

profiles of absorbance at 420 nm are shown in (b). The black trace is from a H2O2 control experiment, while the red

trace is from one of the OH oxidation experiments.

We propose that the observed trend during OH oxidation is due to initial functionalization followed

by ring-cleavage reactions. Previous studies (Sun et al. 2010) have shown that OH oxidation leads

to hydroxylation of the aromatic ring, in analogy to the gas phase (Atkinson 1990). The additional

hydroxyl group is electron donating, with its lone pair electrons contributing to the conjugation

and leading to enhanced absorption. We note that oligomeric products have also been reported

from OH oxidation of phenolic compounds (Sun et al. 2010, Chang and Thompson 2010). In

particular, Chang and Thompson have observed significant enhancement of absorption, and they

proposed that the absorption is attributed to HULIS produced from phenol OH oxidation. To

simulate cloudwater chemistry, we used nitrophenol concentrations orders of magnitude lower

than those used in Chang and Thompson and so we consider the formation of oligomers less

important in our system.

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To quantitatively assess the formation and decay rate of color, we applied a kinetic model

framework based on the absorbance at 420 nm (Figure 5.9a). The OH radical concentration is

assumed to be in steady state at 3.2 × 10-13 M which is the average of measured [OH]ss using the

Aerosol CIMS method. The nitrophenol precursor (NP) follows a prescribed pseudo 1st order

decay with a rate constant, kINP, which is estimated based on 4NP OH reactivity reported by

Einschlag et al. (2003). A colored product (CP) is formed from NP with a pseudo 1st order rate

constant kIcolor, but simultaneously undergoes photo-bleaching with another pseudo 1st order rate

constant kIbleach. Although NP can likely give rise to more than one CP species, the colored products

are lumped into a single compound for simplicity. The sum of absorbance from NP and CP is

treated as the total absorbance of the solution. We found the optimal combination of kIcolor and

kIbleach values that minimizes the sum of the squared difference between the modelled and the

observed absorbance change. We note that kIcolor and kI

bleach are absorbance-based rate constants

and should not be confused with concentration-based rate constants. If the identity and molar

absorptivity of CP are characterized in future studies, these absorbance-based rate constants can

be converted into concentration-basis.

The results for one 4NC experiment are shown in Figure 5.9b. The two shaded areas in Figure 5.9b

represent modeled absorbance due to the precursor, 4NC, and the CP, respectively. The red trace

is the absorbance change measured during the experiment shown in Figure 5.8. Results for 4NP

and 5NG, along with detailed model conditions are included in the Appendix C, Section C8. For

all three nitrophenols, this model captures the initial increase and later decay of color, but the time

at which the absorbance reaches its maximum and the decay rate at the end of the experiment are

more difficult to match. This is perhaps due to the fact that nitrophenols form multiple generations

of colored products, giving rise to a more dynamic evolution of absorbance than the current model

framework can produce. Nevertheless, the model represents a novel effort to estimate the rates of

photo-enhancement and bleaching during OH oxidation of nitrophenols. The optimal kIcolor and

kIbleach values for the three nitrophenols are listed in Table 5.3. Since these values are all psudo-1st

order rate constants, their corresponding second order rate constants (kIIcolor and kII

bleach) are also

calculated using Eqn. 5.2 and provided in Table 5.3. The values reported in Table 5.3 are the

average of two replicates performed for each nitrophenol. Relative errors are roughly 10 % for

4NP and 5NG, and 15 % for 4NC.

170

Figure 5.9: A schematic illustration of the simple kinetic model (a) and one example of 4NC photooxidation (b). The

shaded areas in (b) are the contributions from a newly formed colored product (CP) and the decaying 4NC,

respectively. The red line follows data from an experiment.

Table 5.3: Photo-enhancement and bleaching rate constants1 for nitrophenol OH oxidation determined from a simple

kinetic model (Section 5.3.3.2.).

Compound kIcolor (s

-1) kIIcolor (M

-1 s-1) kIbleach (s

-1) kIIbleach (M

-1 s-1)

4-nitrophenol 8.5 × 10-4 2.6 × 1010 3.8 × 10-4 1.2 × 1010

5-nitroguaiacol 3.9 × 10-3 1.2 × 1011 2.0 × 10-3 6.1 × 1010

4-nitrocatechol 3.3 × 10-3 1.0 × 1011 4.6 × 10-3 1.4 × 1011

1The rate constants are absorbance-based and should be distinguished from concentration-based rate constants.

Values reported here are the average of two replicates.

171

5.3.3.3 Atmospheric Fate of Nitrophenols

Our results indicate that the photo-bleaching by OH oxidation is rapid and presents the dominant

fate for BrC represented by nitrophenols. As the [OH]ss in our experiment (3.2 × 10-14 M) is

roughly that of cloudwater in remote areas (Herrmann et al. 2010), the light absorptivity of

nitrophenols is expected to reach its maxima and to be bleached within one hour of in-cloud time.

On the other hand, photo-enhancement during direct photolysis is much slower, with color forming

over a time scale of hours. This observation agrees with Vione et al. (2009) who also determined

radical chemistry as the dominant sink of 4NP compared to direct photolysis. That being said, this

trend may not apply to all nitrophenols. For instance, dinitrophenols represent an interesting group

of compounds to investigate in the future, as the additional nitro group deactivates OH radical

reactions (Einschlag et al. 2003) but enhances light absorption (Schwarzenbach et al. 1988).

172

Figure 5.10: Direct photolysis of the WSOC from biofuel combustion samples. The spectral evolution of the kaoliang

and the cotton samples is shown in (a) and (b), respectively. The color code indicates illumination time, while the

insets show the absorbance change compared to the initial condition. The time profiles of absorbance at three different

wavelengths for the same samples are shown in (c) and (d), respectively.

5.3.4 Direct Photolysis of WSOC from Biofuel Combustion Samples

A change in absorptivity was observed when WSOC from biofuel combustion samples was

exposed to simulated sunlight. Results for the kaoliang stalk sample and the cotton stalk sample

are shown in Figure 5.10a and 10b, respectively. Their absorbance changes at three wavelengths

(350, 400 and 420 nm) are also shown in Figure 5.10c and 5.10d, respectively. WSOC from the

two samples exhibited different trends, with the kaoliang stalk sample showing a temporary photo-

enhancement shortly after the initiation of illumination, and the cotton stalk sample exhibiting

monotonous photo-bleaching. The trends for the sample at different wavelengths demonstrate the

complexity of the real biomass burning samples. Our results provide qualitative evidence that the

optical properties of WSOC extracted from BB BrC can change upon photochemistry.

5.4 Conclusions and Atmospheric Implications

The overall conclusion from this work is that because atmospheric brown carbon species are

organic chromophores and susceptible to photochemical degradation, their optical properties are

altered by aqueous-phase photochemical processing with both photo-enhancement and photo-

bleaching possibly occurring. In particular, Imine-mediated BrC, arising from aqueous-phase

reactions between carbonyl compounds and nitrogen-containing nucleophiles, undergoes rapid

photo-bleaching via both direct photolysis and OH oxidation. Bleaching of glyoxal-ammonium

sulfate (GLYAS) BrC was predominantly driven by OH oxidation whereas that for methylglyoxal-

ammonium sulfate (MGAS) was driven by direct photolysis. Three species of nitrophenols were

investigated as an important subset of biomass burning BrC. Photo-enhancement of absorption

was observed when the nitrophenol species are illuminated with simulated sunlight, as well as

during the initial stages of OH oxidation. Although such photo-enhancement can potentially

magnify the direct radiative effect of nitrophenols, photo-bleaching of nitrophenols with further

OH exposure was observed to be also rapid. This is the first investigation of OH oxidation induced

effects on the optical properties of BrC, demonstrating its importance in determining the

173

atmospheric significance of BrC. Lastly, a study of biofuel BrC species illustrated that the optical

properties of ambient samples are also rapidly altered. These findings are in general agreement

with prior studies that have also seen evidence for photo-bleaching (Lee et al. 2014b, Zhong and

Jang 2014, Sareen et al. 2013).

Using atmospherically relevant light levels and aqueous OH concentrations, the timescales for

these changes are all rapid, i.e. on the order of an hour or less. This indicates the atmospheric

concentrations of BrC species will be highest during the night, when their atmospheric significance

for shortwave radiative forcing is zero. For example, in the case of the Imine BrC species, they

may form slowly during the night in cloud or aerosol water and then will decay away rapidly in

the morning. It is expected that during the daytime their steady state concentrations will be highest

in regions where there is considerable droplet evaporation proceeding. Biomass burning BrC

emitted during the night time will be stable. Upon sunrise, photochemistry can induce photo-

enhancement, but the BrC concentration will also fall with further photochemical processing. The

magnitude of photo-enhancement and bleaching is likely dependent to the BrC components, as

well as OH exposure. We conclude that atmospheric models that include only source functions

and depositional loss rates for BrC-bearing organic aerosol will misrepresent the radiative impacts

of these particles, requiring additional parameterizations for photo-bleaching and photo-

enhancement.

Whereas this paper has focused upon aqueous phase processing, it will be important to also assess

the rates of heterogeneous oxidation of BrC species in particles via interactions with gas phase

oxidants and to study direct photolysis in aerosol particles.

Acknowledgement

The authors thank Dan Mather and Ying Lei for the TOC measurement, Wendy Zhang at

Environment Canada for preparing the filter samples, and Andre Simpson and Liora Bliumkin at

University of Toronto Scarborough for useful discussions and trial measurements. Funding for this

work came from NSERC and Environment Canada.

Supplementary Information

174

Supplementary Information for this chapter is given in Appendix C.

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Chapter 6

Cloud Partitioning of Isocyanic Acid (HNCO) and Evidence of

Secondary Source of HNCO in Ambient Air

Reproduced with permission from Geophysical Research Letter (41), pp 6962–6969

DOI: 10.1002/2014GL061112 Copyright © 2014 American Geophysical Union.

182

Abstract

Although isocyanic acid (HNCO) may cause a variety of health issues via protein carbamylation

and has been proposed as a key compound in smoke-related health issues, our understanding of

the atmospheric sources and fate of this toxic compound is currently incomplete. To address these

issues, a field study was conducted at Mount Soledad, La Jolla, CA, to investigate partitioning of

HNCO to clouds and fogs using an Acetate Chemical Ionization Mass Spectrometer coupled to a

ground-based counterflow virtual impactor. The first field evidence of cloud partitioning of HNCO

is presented, demonstrating that HNCO is dissolved in cloudwater more efficiently than expected

based on the effective Henry’s law solubility. The measurements also indicate evidence for a

secondary, photochemical source of HNCO in ambient air at this site.

6.1 Introduction

Isocyanic acid (HNCO) has been proposed to be a key compound in smoke-related health issues.

In particular, a previous study (Wang et al. 2007) implied a potential connection between HNCO

and protein carbamylation, a process giving rise to a series of health impacts such as cataracts,

rheumatoid arthritis, and cardiovascular diseases (Roberts et al. (2010) and references herein).

Studies of HNCO in the ambient atmosphere, however, have been limited by the lack of

appropriate measurement methods. In situ detection of ambient HNCO has become possible only

since the development of Acetate Chemical Ionization Mass Spectrometry (Acid-CIMS) for the

detection of acid species by Roberts and coworkers (Veres et al. 2008, Roberts et al. 2011, Roberts

et al. 2014). As the Acid-CIMS has been deployed only recently, our understanding of the

atmospheric processing of HNCO remains incomplete.

It is well known that formation of HNCO is associated with pyrolytic processes, having been

detected from pyrolysis of coals (Nelson et al. 1996), nitrogen-containing polymers (Karlsson et

al. 2001), and selected biomass (Hansson et al. 2004). Using the Acid-CIMS, Roberts and

coworkers have further confirmed that HNCO can be directly emitted from biomass burning and

cigarette smoke (Roberts et al. 2010, Veres et al. 2010). Other recent studies (Krocher et al. 2005,

Heeb et al. 2011, Wentzell et al. 2013) have detected HNCO from diesel exhaust and as a by-

product of urea selective catalytic reduction of nitrogen oxides. Relatively unknown to the

183

community is a potential photochemical source of HNCO that has been implicated by very recent

field measurements (Roberts et al. 2011, Wentzell et al. 2013, Roberts et al. 2014) and a laboratory

study of amine oxidation (Borduas et al. 2013). A secondary source has not been incorporated into

global chemical transport models (Young et al. 2012), and the magnitude and mechanism of this

source must be characterized through field and laboratory studies.

In terms of atmospheric sinks, HNCO is resilient against OH oxidation (Tsang 1992) and direct

photolysis (Dixon and Kirby 1968) but is reasonably water soluble, with an effective Henry’s law

constant reaching several thousand M atm−1 at cloudwater-relevant pH values (Roberts et al. 2011).

Therefore, the major sink of HNCO is considered to be via aqueous phase processes. In addition,

it has been shown that the acid-catalyzed hydrolysis reaction can lead to irreversible loss of HNCO

in the aqueous phase (Belson and Strachan 1982). A recent modeling study (Barth et al. 2013)

found that the atmospheric lifetime of HNCO can be a few hours or less in lower level clouds,

depending on the pH of the cloud and temperature. Thus, the degree to which HNCO partitions to

cloudwater plays a crucial role in governing the atmospheric lifetime of HNCO.

Given that there have been no direct field observations of HNCO cloud scavenging, field

measurements were performed at an elevated site near La Jolla, CA, where clouds are often

prevalent, and the area offers a wide range of potential sources of HNCO. In this paper, we report

the first direct detection of HNCO in cloudwater by coupling the Acid-CIMS to a ground-based

counterflow virtual impactor (CVI). We also present evidence of a photochemical source of HNCO

in the ambient air which, at this site, is more significant than its primary source.

6.2 Methods

6.2.1 Site Description

The measurements were conducted near La Jolla, CA (32.8400◦N, 117.2769◦W), from 1 May to

18 June 2012 at a sampling site located near the peak of Mount Soledad (approximately 230 m

above sea level; see Section D1 in Appendix D). During this season, the prevailing wind was

northwesterly (i.e., from the ocean). A back trajectory analysis for this study (Schroder et al. 2014)

suggests that the air mass lifted from closer to the ocean surface 10 to 20 h prior to sampling of

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the cloud at the site. The low-lying clouds sampled at the site have likely arisen from such

advection of marine moisture, nighttime cooling, and lift driven by the low coastal hills.

Other instruments at the Mount Soledad site include a Fog Monitor (FM-100; Droplet

Measurement Technologies (DMT)) to measure ambient liquid water content and droplet size

distribution, a California Institute of Technology Active Strand Cloudwater Collector Version 2,

a single-particle soot photometer (DMT) for black carbon measurement, and a suite of gas phase

and particle size analyzers.

6.2.2 Acid-CIMS

The Acid-CIMS is a chemical ionization mass spectrometry (CIMS) technique utilizing acetate

(Ac−) as the reagent ion. In the current study, the analytes were likely detected via the reaction

represented by Eqn. 6.1 (Veres et al. 2008, Bertram et al. 2011).

Ac−+ MH → AcH + M−. (6.1)

Due to the weak gas phase acidity of Ac−, sample molecules that bear acidic protons (MH) transfer

a proton to Ac− and are detected as M−. However, we cannot rule out the possibility that cluster

formation and fragmentation may also have contributed to the mass-to-charge ratio (m/z) of

interest. The Acid-CIMS can detect a wide range of organic and inorganic acids. Some detectable

species are summarized by Veres et al. (2008). The Acid-CIMS instrument used is a quadrupole

CIMS which has been described elsewhere (Wentzell et al. 2013). For the ambient measurement,

the entire inlet line was externally heated to 80 ◦C to minimize surface loss. The inlet flow was

bypassed to a carbonate denuder every 30 min to scrub gas phase acids and obtain a background

measurement. Calibrations for the acid species were performed in the laboratory before and after

the field measurement. The method of HNCO calibration, calibration factors, and the limit of

quantification for HNCO and nitric acid (HNO3) are listed in Section D2 in Appendix D.

6.2.3 CVI

A ground-based CVI from University of Stockholm was employed to sample cloud droplets while

excluding cloud interstitial particles and gases. The sampled droplets were subsequently dried, and

properties of the residual particles and gases were then measured with a variety of instrumentation.

The operation of the CVI has been described elsewhere (Noone et al. 1988, Noone et al. 1988, Lee

185

et al. 2012). Briefly, the combination of a lower intake flow rate and a warm, dry, and clean

counterflow create a virtual stagnant plane of air inside the tip of the CVI, whereby only larger

particles with sufficient inertia to move through the counterflow out of the tip and reach the

stagnant region can be sampled. The 50% cutoff diameter of the CVI (i.e., the cut size of cloud

droplets sampled by the CVI) is calculated at 11.5 ± 0.7 μm. Once sampled, these cloud droplets

are subject to evaporation due to exposure to the dry, warm part of the counterflow that carries the

droplets/particles to the instrumentation. In previous studies, the ground-based CVI was employed

to investigate the chemical composition of the particulate residuals of cloud droplets and

partitioning of H2O2 (Noone et al. 1991).

The novelty of the current study lies in the coupling of the Acid-CIMS to the CVI, along with an

Aerodyne high-resolution time-of-flight aerosol mass spectrometer (DeCarlo et al. 2006). The

application of the CIMS downstream of the CVI enabled the measurements of organic and

inorganic acids evaporating out of cloud droplets in real time. Such an in situ method is required

for the measurement of cloudwater HNCO, given that it will hydrolyze before off-line

measurements can be performed. In the current study, the ambient sampling inlet was manually

switched to the CVI just prior to the cloud arrival.

6.3 Results and Discussion

6.3.1 Detection of HNCO From Cloudwater

The Mount Soledad site experienced three major cloud events during the campaign. All of these

events began during the night or early morning and terminated before noon. In the current paper

we use the events on 31 May to 1 June (the June 1st event) and on 12 June to 13 June (the June 13th

event) only, as the cloud liquid water content (LWC) during these two cloud events was higher

and all instruments were performing optimally. HNCO was detected from cloudwater along with

HNO3. Detailed descriptions for the quantification of HNCO and HNO3 in the CVI can be found

in Section D3 in Appendix D.

Figures 6.1a and 6.1b highlight the first 3 h of the two cloud events. The mixing ratios of HNCO

and HNO3 detected after the CVI ([HNCO]CVI and [HNO3]CVI) exhibited good correlations with

the ambient LWC, with the R2 values reaching 0.55 and 0.47 during the two events (Figure 6.1c).

186

This implies that HNCO is present in cloudwater and can be detected and that dissolved HNCO

can partition back to the gas phase if the cloud droplet evaporates before HNCO is hydrolyzed.

This verifies the modeling results by Barth et al. (2013), where the partitioning of HNCO was

determined to be reversible.

Figure 6.1: Time series of HNCO and HNO3 mixing ratios measured after the CVI during (a) the June 1st event and

(b) the June 13th event are shown along with LWC in the surrounding air. (c) The correlations of HNCO with LWC

for both of the events are shown.

6.3.2 Estimation of the Aqueous Fraction of HNCO (faq,HNCO)

To estimate the air-cloud partitioning of HNCO, the aqueous fraction of HNCO (faq,HNCO) is

calculated. The faq,HNCO is defined as the fraction of total HNCO present in the aqueous phase in a

unit volume of air with LWC of 0.1 g m−3. This LWC value was chosen because it is approximately

the median of LWC observed in the cloud events (Figure 6.1).

187

The calculation of faq,HNCO was conducted by taking the mixing ratio of HNCO immediately prior

to the cloud events ([HNCO]precloud, shown in Table 6.1) as the total amount of HNCO in the gas

phase and assuming that this amount is equal to the total of HNCO in the cloud ([HNCO]CVI) and

in the interstitial air after the cloud arrival. This method assumes constant atmospheric conditions

before and after the arrival of the cloud. Only the first 3 h of the two cloud events were used

because the diurnal profile of HNCO indicates that the ambient mixing ratio of HNCO is usually

stable at night, with no significant variation for several hours. Given the assumptions above,

faq,HNCO can be represented by the ratio of [HNCO]CVI to [HNCO]precloud. However, this calculation

is dependent upon CVI parameters such as the droplet size cutoff (i.e., the fraction of droplets

sampled by the CVI), the enhancement factor, and droplet transmission in the CVI (Noone et al.

1988). The detailed calculation of faq,HNCO and detailed descriptions of each term are provided in

Section D4 in Appendix D. The time series of the calculated faq,HNCO exhibited significant scatter

but had a relatively constant average in each cloud event. The average faq,HNCO values calculated

for the June 1st and 13th events are 17 ± 3.2% and 7 ± 1.3%, respectively (Table 6.1). The

uncertainty range arises from a relative error of 19%, which we estimated based on the variation

of the parameters used for its calculation (see Section D4.4 in Appendix D).

6.3.3 Unexpectedly High Aqueous Fraction of HNCO

The effective Henry’s law constant (KHeff) of HNCO is highly pH dependent (Roberts et al. 2011),

with an exponential increase at high pH due to enhanced acid dissociation. Given that the pH

values of collected cloudwater samples during the two cloud events were 5.95 and 4.2, the

theoretical faq,HNCO can be calculated (see Section D5 in Appendix D) to be 0.7 % and 0.02 % for

the two events. The observed faq,HNCO values (Table 6.1) qualitatively agree with the pH

dependence of the HNCO partitioning; i.e., a higher faq,HNCO was observed when the cloud pH was

higher in the June 1st event. However, the magnitude of the faq,HNCO is much larger than the

theoretical values. Based on the pH dependence of KHeff, the observed faq,HNCO value on 1 June of

17% corresponds to a pH value as high as 7.35.

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Table 6.1: Summary of the Aqueous Fraction of HNCO (faq,HNCO) Measured and Calculated

1 Measured from the cloudwater sample collected by the cloudwater collector.

2Calculated from the cloudwater bulk pH and effective Henry’s law constant of HNCO reported by Roberts et al.

(2011).

A potential explanation for the high faq,HNCO is the size dependence of cloudwater acidity, with

larger droplets being less acidic. Different solute composition likely causes the difference between

the smaller (more sulfate) and larger (more sea salt) droplets (Noone et al. 1988). While the CVI

sampled droplets are larger than 11.5 μm, the cloudwater collector had a much lower size cutoff

(diameter = 3.5 μm); thus, the bulk cloudwater pH values represent the average across a wider

range of droplet size. The large droplets, to which more of the HNCO was likely scavenged, might

have been less acidic, giving rise to a higher KHeff value of HNCO.

Entrainment of cloud-free air into a cloud environment can also potentially affect the partitioning

of HNCO in cloud droplets. The entrainment process has been widely investigated in terms of how

it may affect cloud microphysical processes (Baker et al. 1980, Baker 1992). From measurements

of H2O2 in cloud residuals downstream of a CVI, Noone et al. (1991) proposed entrainment as a

possible way to lead to systematic deviations from Henry’s law equilibrium. They showed that

entrainment can supply H2O2 to the cloud air mass if the concentrations outside cloud are higher

than in cloud. Similar phenomenon may occur to HNCO considering that HNCO in clouds can be

depleted due to hydrolysis. However, this data set does not allow us to assess the extent to which

entrainment may influence the partitioning of HNCO.

June 1st Event June 13th Event

[HNCO]pre-cloud (pptv) 48 115

Bulk pH1 5.95 4.2

faq,HNCO measured 17 ± 3.2 % 7 ± 1.3 %

faq,HNCO theoretical2 0.7 % 0.02%

189

Potential systematic errors of the obtained faq,HNCO values are now discussed, given that this is a

particularly challenging measurement. The first arises from the CVI and the pre-cloud mixing ratio

of HNCO. A sensitivity analysis (see Section D4.5 in Appendix D) was performed by

systematically varying each parameter of the CVI and [HNCO]precloud, but the calculated faq,HNCO

was still higher by a factor of 2 than predicted based on its KHeff. We conclude that variations on

this order in the CVI parameters and the pre-cloud mixing ratio of HNCO cannot fully explain the

high faq,HNCO.

Related to this, the assumption that [HNCO]precloud is equal to the total of cloud and interstitial

concentration of HNCO presents another significant uncertainty. This assumption is often applied

to stagnant clouds such as a radiation fog (Collett et al. 2008), where the atmospheric composition

does not change much before and after the cloud formation. However, the clouds observed in the

current study have a strong advection component in addition to the likelihood of enhancement due

to nighttime cooling, making it difficult to assess whether the same air masses are being sampled

before and after the cloud arrives at the sampling site (Schroder et al. 2014). Similarly, primary

emissions into the cloud could have occurred. However, we note that the ratio of HNCO to LWC

remains constant to within a factor of 2 during the first 3 h of each event (Section D4 in Appendix

D). We believe that this is an indication that the pre-cloud amount of HNCO is steady to this level

of precision.

Finally, the total amount of HNCO in the cloud could have decreased due to hydrolysis which has

been shown to be pH dependent, as mentioned previously. At cloud pH of 4.2 (i.e., the June 13th

event), the hydrolysis lifetime can be as short as 2 h (Roberts et al. 2011). In this regard, though,

hydrolysis can only lead to underestimates of faq,HNCO.

6.3.4 Evidence of a Secondary Source of HNCO in the Ambient Air

When clouds are absent at the measurement site, the Acid-CIMS measured HNCO in the ambient

air. A clear diurnal profile of the HNCO mixing ratio was observed (Figure 6.2a). The absence of

episodic spikes of HNCO indicates minimal influence from biomass burning. Also seen in Figure

6.2 is a strong correlation between HNCO and HNO3, a secondary species produced

photochemically (Finlayson-Pitts and Pitts 2000) but not between HNCO and BC, a primary

species. The diurnal profile indicates that the mixing ratio of HNCO typically reached its

maximum at noon, very similar to HNO3 but at a significantly different time from BC (Figure

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6.2b). HNCO also correlates well with other photochemically produced species (formic acid and

ozone) and the ambient temperature, as shown in Section D6 in Appendix D.

Figure 6.2: The time profile of HNCO and HNO3 measured during a selected period of (a) the campaign and (b) the

averaged diurnal profiles of HNCO, HNO3, and black carbon (BC) from the entire campaign, where the error bars

represent 1𝜎 of the diurnal variation. (c) The primary-secondary apportionment of HNCO is shown. See text for details

about the apportionment.

The strong correlation between HNCO and ambient temperature requires specific concern because

it implies that HNCO might have arisen from surface evaporation (e.g., from ground surface,

aerosol, and cold spots on the inlet line). To test this possibility, we further performed correlation

191

analyses between HNCO and various species for each day (Figure 6.3). It was observed that the

correlations between HNCO and formic acid, HNO3, and ambient temperature were much stronger

during the day than the night (Figures 6.3a to 6.3c). The differences have been shown to be

statistically significant using the paired t test. The weak nighttime correlation and strong daytime

correlation between HNCO and the ambient temperature implies that HNCO has not likely arisen

from surface evaporation which should lead to equally strong correlation during both daytime and

nighttime. HNCO and temperature were likely both influenced by a daytime factor such as solar

radiation. The correlations between BC and temperature (Figure 6.3d), on the other hand, were

uniformly low across the three time periods.

The above observations are evidence of a secondary, photochemical source of HNCO at the

measurement site, complementary to observations from recent field studies (Wentzell et al. 2013,

Roberts et al. 2014). The mechanism of secondary HNCO formation is poorly characterized. As a

possible formation pathway of HNCO, Borduas et al. (2013) recently proposed its formation from

photooxidation of an amine (i.e., monoethanolamine) via an amide intermediate which is known

to give rise to HNCO upon photooxidation (Barnes et al. 2010).

We note that the diurnal profile of HNCO exhibits a sharp rise in the early morning (Figure 6.2b),

resembling that of BC. The correlation of HNCO with BC during the morning rush hours (5 A.M.

to 8 A.M.) is generally stronger than other times during the day (Section D7 in Appendix D). This

implies that a primary source of HNCO may also be present at the measurement site, knowing that

diesel exhaust can contain HNCO (Wentzell et al. 2013).

A simple primary versus secondary apportionment for HNCO sources was performed using the

observed diurnal profiles of HNCO, BC, and O3. Assuming that the primary HNCO exhibits a

similar diurnal trend as that of BC, the secondary HNCO can be calculated as the difference

between the observed total HNCO and primary HNCO. We scaled primary HNCO until the rise

of secondary HNCO matched the rise of the O3 diurnal profile (Figure 6.2c). The area under the

primary and secondary HNCO diurnal profile acts as an estimate of their relative contribution. As

shown in Figure 6.2c, secondary HNCO is roughly twice primary HNCO, indicating that

photochemistry is likely the dominant source of HNCO at the sampling site.

192

Figure 6.3: The time profile of HNCO and HNO3 measured during a selected period of (a) the campaign and (b) the

averaged diurnal profiles of HNCO, HNO3, and black carbon (BC) from the entire campaign, where the error bars

represent 1𝜎 of the diurnal variation. (c) The primary-secondary apportionment of HNCO is shown. See text for details

about the apportionment.

6.4 Summary

This study represents the first time that dissolved gases in cloudwater have been detected in an

online manner, focusing on the cloud scavenging of isocyanic acid (HNCO). In particular, HNCO

evolving from cloud droplet evaporation was detected by an Acid-CIMS coupled to a counterflow

193

virtual impactor (CVI). By estimating the aqueous fraction of HNCO, we find that HNCO may be

scavenged by cloudwater more efficiently than predicted from its effective Henry’s law constant.

This observation confirms that aqueous phase partitioning plays a crucial role in determining the

atmospheric lifetime of this toxic compound. The reason for such significant partitioning is

currently unclear and is a direction for future research. Meanwhile, we observed HNCO

repartitioning to the gas phase once cloud droplets evaporate, confirming the reversibility of this

process (Barth et al. 2013).

We also show evidence of a secondary, photochemical source of HNCO in the ambient air,

consistent with selected observations from previous field and laboratory studies. Our results show

that photochemistry may be the dominant source of HNCO in an environment where the influence

of biomass burning is minimal. This secondary source needs to be considered for applications

where HNCO is used as a tracer of biomass burning. The mechanism and kinetics of secondary

formation of HNCO need to be investigated before it can be incorporated into a global chemical

transfer model.

Acknowledgement

The authors would like to thank Environment Canada, NSERC, and Center for Global Change

Science at University of Toronto for funding and the Russell Research Group for technical support.

The data from this work will be available upon request to the corresponding author.

Supplementary Information

Supplementary information for this chapter is given in Appendix D.

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Chapter 7

Conclusions and Future Research

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7.1 Summary and Future Research for Laboratory Investigations of Aqueous-phase Chemistry

In Chapter 2 and 3, Aerosol CIMS was shown to be a highly valuable technique for online

monitoring of aqueous-phase chemistry. In Chapter 2, the total concentration of the quantified

products exhibited good agreement with the TOC concentration determined independently,

indicating the reliability of quantification using Aerosol CIMS. This was also the first time organic

hydroperoxides were detected from the aqueous-phase using online mass spectrometry,

emphasizing the importance of applying soft-ionization MS techniques. In Chapter 3, the

additional advantages of high mass resolution for this technique was illustrated via employment

of a HR-ToF-CIMS. The novel analysis frameworks, mass defect plot and DBE/#C ratio,

introduced in Chapter 3, can be applied to other systems where high mass resolution MS techniques

are applied to the chemistry of complex organic compounds.

This work and most of the previous investigations for aqueous-phase organic chemistry have

performed experiments in bulk aqueous solutions. While this approach provides fundamental

information about the chemical reactions, it does not fully represent the ambient conditions where

aqueous phases are in a suspended form. Daumit et al. (2014) have recently demonstrated that the

gas-aqueous partitioning of organic compounds is significantly different between bulk aqueous

solutions and suspended aqueous droplets, driven by differences in LWC. The faq as a function of

Heff at the bulk LWC (106 g m-3) is added to Figure 1.2 for comparison (Figure 7.1). As there is

little gas phase in a bulk solution, even the least water soluble compounds may stay entirely in the

aqueous phase. Daumit et al. (2014) have also shown that reaction products forming in the

aqueous-phase are affected in the same way, giving rise to significant difference in SOA yield

between the bulk solution and suspended droplets. In the future, it is important that experiments

be conducted using suspended droplets, as has been done already by several pioneering studies

(Nguyen et al. 2013, Wong et al. 2014).

Chapter 2 and the majority of previous investigations on aqueous-phase processing have focused

on precursors introduced to the aqueous-phase via dissolution from the gas phase, primarily by the

uptake of small carbonyl and dicarbonyl compounds. The chemistry of these precursors is

important, given that it is unrecognized by the traditional gas-particle partitioning theory, where

partitioning to an organic phase prevails. However, these precursors only comprise a small

200

fraction of the total DOC (Herckes et al. 2013). In fact, the majority of DOC is likely introduced

to the aqueous-phase via nucleation scavenging (Ervens et al. 2013). Hindered by the chemical

complexity, aqueous-phase processing of DOC has been investigated by only a small number of

studies (Bateman et al. 2011, Aljawhary et al. 2013, Nguyen et al. 2013). Understanding DOC

evolution during photochemical processes is a critical, yet unexplored research direction. The

Aerosol-ToF-CIMS setup with the novel analysis framework introduced in Chapter 3 is highly

suited for this purpose.

Figure 7.1: Calculated aqueous fraction (faq) as a function of effective Henry’s law constant Heff. The figure

is same as Figure 1.2, but with the addition of faq at bulk LWC (106 g m-3), where chemicals exist entirely

in the aqueous phase.

7.2 Summary and Future Research for Organic Hydroperoxide (ROOH) Formation

In Chapter 4, the formation equilibrium constants for a variety of α-HHP species were quantified.

α-HHP was observed from aldehydes, but not from ketones and methacrolein. It was concluded

that α-HHP may be important in ALW, enhancing the Heff of aldehyde species. While reports of

detection of ROOH in atmospheric aqueous phases are sparse, Chapter 4 demonstrated that ROOH

may present, but existing methods have not been able to detect it. Paulson and coworkers (Hasson

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and Paulson 2003, Arellanes et al. 2006, Wang et al. 2011) have detected unexpectedly high

concentrations of H2O2 from filter extracts. This might be due to the fact that ROOH species have

decomposed during the extraction process, giving rise to H2O2. Given the importance of ROOH

as a reactive oxygen species and as a reservoir of HOx, its fate in atmospheric aqueous phases

should be further investigated.

As ROOH arises from the RO2 + HO2 chemistry (Figure 1.6 (i)), its formation during aqueous-

phase OH oxidation of organic compounds is likely. However, the majority of MS techniques

cannot distinguish ROOH from structural isomers. One approach to overcome this issue is to

optimize the voltages of ion transmission in the mass spectrometer to find a signature

fragmentation pattern for ROOH species. This approach has been successful in detecting gas-phase

ROOH species using a CF3O- CIMS developed by Wennberg and coworkers (Crounse et al. 2006,

St Clair et al. 2010). Another approach is to combine offline chemical assays with the online

approach used in Chapter 2 and 3. Chemical assays such as those based on dichlorofluorescin

(Venkatachari et al. 2005) and iodide (Docherty et al. 2005) are useful in quantifying total ROOH

concentration in solutions. Along this line of thought, an interesting investigation will be to vary

the initial concentration of the precursor organic compounds to examine the yield of ROOH

species. It is expected that higher organic concentrations facilitate RO2 + RO2 chemistry which

does not give rise to ROOH.

7.3 Summary and Future Research for Atmospheric Brown Carbon (BrC)

Chapter 5 demonstrated that photochemical processing in the aqueous-phase significantly altered

the light absorptivity of BrC species. The rate at which photo-enhancement and photo-bleaching

occur should be further quantified. Given that the work conducted in Chapter 4 did not offer

molecular information for the BrC species and their reaction products, the immediate next step

would be their identification. As imine-BrC and ambient BrC comprises highly complex organic

mixtures, chromatographic separation should be employed prior to MS analysis. A high

performance liquid chromatography – diode array detection – electrospray ionization (HPLC-

DAD-ESI) MS technique is highly suited for this purpose, as the separation, absorption and MS

202

detection are integrated in one system. Once the BrC species and their products are identified, the

absorbance-based modeling approach employed in Chapter 5 can be converted to a concentration

basis, and the rate constants will gain more applicability to atmospheric models.

The poly-carbonyl intermediates observed in OH oxidation of levoglucosan (Chapter 3) contain

extensive electron conjugation and may represent a class of unrecognized BrC that arises from

other sugars and polyols. Sugars are abundant in the atmosphere, arising from biological sources

(Wan and Yu 2007), while polyols are produced from condensed-phase chemistry of isoprene

epoxydiols (Surratt et al. 2010). OH oxidation of these compounds may give rise to similar poly-

carbonyl intermediates observed in Chapter 3 and deserves further investigation. As mentioned in

Section 7.1, the experiment should be conducted in suspended droplets to better represent the gas-

aqueous partitioning taking place in the atmosphere. Photo-acoustic absorption spectrometry

(PAS) is currently the only method able to directly monitor particle absorptive properties and

should be further optimized and applied in laboratory experiments.

7.4 Summary and Future Research for Cloud Partitioning of Organic Compounds

In Chapter 6. the faq of isocyanic acid (HNCO) was measured in the field. By coupling online MS

downstream of a CVI, this work demonstrated the first online measurement of organic compounds

dissolved in ambient cloudwater. HNCO was for the first time detected from ambient cloudwater,

and its partitioning to cloudwater was shown to be more significant than expected from its Heff.

Models commonly assume Henry’s law equilibria for gas-aqueous partitioning of water soluble

organic compounds (Carlton et al. 2008, McNeill et al. 2012), but field confirmation for this

assumption is lacking. The ambient atmosphere is highly dynamic, and Henry’s law equilibria may

or may not be established. Noone et al. (1991) have observed that entrainment (i.e. introduction of

dry air to in-cloud air) perturbed the in-cloud Henry’s law equilibrium of H2O2. The presence of

highly concentrated salts in ALW may also cause deviation from Henry’s law equilibrium (Kroll

et al. 2005, Wang et al. 2014). On the other hand, measurements of scavenging efficiency of

organic compounds by nucleation scavenging are also sparse (Herckes et al. 2013). More field

203

measurements integrating the gas and particle aqueous phases should be conducted to better

quantify Heff and scavenging efficiency in the ambient atmosphere.

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(ToF-CIMS): application to study SOA composition and processing., Atmos. Mea. Tech., 6, 2013.

Arellanes, C., Paulson, S., Fine, P. and Sioutas, C.: Exceeding of Henry's law by hydrogen

peroxide associated with urban aerosols, Environ. Sci. Technol., 40, 4859-4866, 2006.

Bateman, A. P., Nizkorodov, S. A., Laskin, J. and Laskin, A.: Photolytic processing of secondary

organic aerosols dissolved in cloud droplets, Phys. Chem. Chem. Phys., 13, 12199-12212, 2011.

Carlton, A. G., Turpin, B. J., Altieri, K. E., Seitzinger, S. P., Mathur, R., Roselle, S. J. and Weber,

R. J.: CMAQ Model Performance Enhanced When In-Cloud Secondary Organic Aerosol is

Included: Comparisons of Organic Carbon Predictions with Measurements, Environ. Sci.

Technol., 42, 8798-8802, 2008.

Crounse, J. D., McKinney, K. A., Kwan, A. J. and Wennberg, P. O.: Measurement of gas-phase

hydroperoxides by chemical ionization mass spectrometry, Anal. Chem., 78, 6726-6732, 2006.

Daumit, K., Carrasquillo, A., Hunter, J. and Kroll, J.: Laboratory studies of the aqueous-phase

oxidation of polyols: submicron particles vs. bulk aqueous solution, Atmos. Chem. Phys., 14,

10773-10784, 2014.

Docherty, K., Wu, W., Lim, Y. and Ziemann, P.: Contributions of organic peroxides to secondary

aerosol formed from reactions of monoterpenes with O3, Environ. Sci. Technol., 39, 4049-4059,

2005.

Ervens, B., Wang, Y., Eagar, J., Leaitch, W. R., Macdonald, A. M., Valsaraj, K. T. and Herckes,

P.: Dissolved organic carbon (DOC) and select aldehydes in cloud and fog water: the role of the

aqueous phase in impacting trace gas budgets, Atmos. Chem. Phys., 13, 5117-5135, 2013.

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Hasson, A. and Paulson, S.: An investigation of the relationship between gas-phase and aerosol-

borne hydroperoxides in urban air, J. Aerosol Sci., 34, 459-468, 2003.

Herckes, P., Valsaraj, K. T. and Collett Jr, J. L.: A review of observations of organic matter in fogs

and clouds: Origin, processing and fate, Atmos. Res., 132, 434-449, 2013.

Kroll, J. H., Ng, N. L., Murphy, S. M., Varutbangkul, V., Flagan, R. C. and Seinfeld, J. H.:

Chamber studies of secondary organic aerosol growth by reactive uptake of simple carbonyl

compounds, J. Geophys. Res. Atmos., 110, D23207, 2005.

McNeill, V. F., Woo, J. L., Kim, D. D., Schwier, A. N., Wannell, N. J., Sumner, A. J. and Barakat,

J. M.: Aqueous-phase secondary organic aerosol and organosulfate formation in atmospheric

aerosols: a modeling study, Environ. Sci. Technol., 46, 8075-8081, 2012.

Nguyen, T. B., Coggon, M. M., Flagan, R. C. and Seinfeld, J. H.: Reactive Uptake and Photo-

Fenton Oxidation of Glycolaldehyde in Aerosol Liquid Water, Environ. Sci. Technol., 47, 4307-

4316, 2013.

Nguyen, T. B., Nizkorodov, S. A., Laskin, A. and Laskin, J.: An approach toward quantification

of organic compounds in complex environmental samples using high-resolution electrospray

ionization mass spectrometry, Anal. Methods, 5, 72-80, 2013.

Noone, K. J., Ogren, J. A., Noone, K. B., Hallberg, A., Fuzzi, S. and Lind., J. A.: Measurements

of the partitioning of hydrogen peroxide in a stratiform cloud, Tellus B, 43, 280-290, 1991.

St Clair, J. M., McCabe, D. C., Crounse, J. D., Steiner, U. and Wennberg, P. O.: Chemical

ionization tandem mass spectrometer for the in situ measurement of methyl hydrogen peroxide,

Rev. Sci. Instrum., 81, 094102, 2010.

Surratt, J. D., Chan, A. W., Eddingsaas, N. C., Chan, M., Loza, C. L., Kwan, A. J., Hersey, S. P.,

Flagan, R. C., Wennberg, P. O. and Seinfeld, J. H.: Reactive intermediates revealed in secondary

organic aerosol formation from isoprene, Proc. Natl. Acad. Sci. U.S.A., 107, 6640-6645, 2010.

Venkatachari, P., Hopke, P. K., Grover, B. D. and Eatough, D. J.: Measurement of particle-bound

reactive oxygen species in rubidoux aerosols, J. Atmos. Chem., 52, 325-326, 2005.

205

Wan, E. C. H. and Yu, J. Z.: Analysis of sugars and sugar polyols in atmospheric aerosols by

chloride attachment in liquid chromatography/negative ion electrospray mass spectrometry,

Environ. Sci. Technol., 41, 2459-2466, 2007.

Wang, C., Lei, Y. D., Endo, S. and Wania, F.: Measuring and Modeling the Salting-out Effect in

Ammonium Sulfate Solutions, Environ. Sci. Technol., 48, 13238-13245, 2014.

Wang, Y., Kim, H. and Paulson, S.: Hydrogen peroxide generation from alpha- and beta-pinene

and toluene secondary organic aerosols, Atmos. Environ., 45, 3149-3156, 2011.

Wong, J. P., Zhou, S. and Abbatt, J. P.: Changes in Secondary Organic Aerosol Composition and

Mass due to Photolysis: Relative Humidity Dependence, J. Phys. Chem. A, 2014.

206

Appendix A

Supplementary Information For:

Chapter 3

Aqueous-phase Photooxidation of Levoglucosan – a Mechanistic

Study Using Aerosol Time-of-Flight Chemical Ionization Mass

Spectrometry (Aerosol ToF-CIMS)

As published in Atmos. Chem. Phys. 14, 9695–9706, 2014. DOI:10.5194/acp-14-9695-2014

Distributed under the Creative Commons Attribution 3.0 License.

207

A1 List of Detected Peaks

Table A1: List of peaks detected by the I(H2O)n- reagent ion. The chemical formulae were assigned using the data

processing software (Tofwerk v. 2.2). The peak time and Max. peak intensity are the illumination time at which each

peak reached its maximum, and its corresponding signal intensity at that time, respectively. The peak intensity has

been normalized by the intensity of the reagent ion at m/z 145 (I(H2O)-). This information, along with the exact m/z

and mass defect were used to construct the mass defect plot (Figure 3.4 in the main article). The compounds displayed

in Figure 3.6 in the main article are color coded.

Detected

Formula

Exact m/z

(Th)

Mass

defect (Th)

Peak time

(min)

Max. peak

intensity Note

CH2O2I 172.911 -0.0895 133 5.76E-03 Formic acid

C2H2O3I 200.905 -0.09458 300 7.91E-03 glyoxylic acid

C2H4O3I 202.921 -0.07893 300 2.92E-03

glycolic acid or

glyoxal

monohydrate

C3H2O3I 212.905 -0.09458 145 1.82E-03 Product (i)

C3H4O3I 214.921 -0.07893 95 7.51E-04 Product (ii)

C2H2O4I 216.900 -0.09967 500 3.00E-03 Oxalic acid

C3H6O3I 216.937 -0.06328 62 1.97E-03

C2H4O4I 218.916 -0.08402 83 1.05E-04

C4H4O3I 226.921 -0.07893 105 1.42E-04

C4H4O3I 226.921 -0.07893 105 1.42E-04

C3H2O4I 228.900 -0.09967 200 8.57E-05

C4H6O3I 228.937 -0.06328 90 3.27E-04

C3H4O4I 230.916 -0.08402 182 6.38E-04

208

C3H6IO4 232.932 -0.06837 141 9.79E-05

C5H4IO3 238.921 -0.07893 97 2.64E-04

C4H2O4I 240.900 -0.09967 101 2.46E-03

C4H4O4I 242.916 -0.08402 105 9.02E-04

C4H6O4I 244.932 -0.06837 79 1.05E-03 Product (iii)

C3H4IO5 246.911 -0.0891 233 6.81E-05

C5H2IO4 252.900 -0.09967 97 1.40E-04

C5H4O4I 254.916 -0.08402 98 2.73E-04

C4H2O5I 256.895 -0.10475 200 4.00E-05

C5H6O4I 256.932 -0.06837 95 3.29E-04

C4H4O5I 258.911 -0.0891 169 9.14E-04 Product (iv)

C5H8O4I 258.947 -0.05272 66 2.65E-04

C4H6O5I 260.927 -0.07345 97 1.37E-04

C3H4IO6 262.906 -0.09419 500 4.00E-05

C5H2O5I 268.895 -0.10475 160 1.40E-04

C5H4IO5 270.911 -0.0891 116 3.79E-04

C5H6IO5 272.927 -0.07345 75 1.31E-03 Product (v)

C5H8IO5 274.942 -0.0578 72 2.33E-04 Product (vi)

C4H6IO6 276.921 -0.07854 151 4.37E-05

C6H4IO5 282.911 -0.0891 102 7.21E-05

209

C6H6O5I 284.927 -0.07345 76 1.02E-03

C6H8IO5 286.942 -0.0578 48 6.49E-03

C6H10IO5 288.958 -0.04215 0 4.49E-02 levoglucosan

C6H2O6I 296.890 -0.10984 260 3.80E-05

C6H4O6I 298.906 -0.09419 136 1.80E-04

C6H6O6I 300.921 -0.07854 97 1.19E-03

C6H8O6I 302.937 -0.06289 81 7.67E-04

C6H10O6I 304.953 -0.04724 46 5.08E-04

C6H4O7I 314.901 -0.09927 220 3.33E-05

C6H6IO7 316.916 -0.08362 200 1.85E-04

C6H8O7I 318.932 -0.06797 97 5.93E-04

C5H6O8I 320.911 -0.08871 330 4.00E-05

C6H10IO7 320.948 -0.05232 59 4.83E-04 Product (vii)

C6H6O8I 332.911 -0.08871 280 8.00E-05

C6H8O8I 334.927 -0.07306 143 1.78E-04

C6H10O8I 336.943 -0.05741 61 1.34E-04

C6H8O9I 350.922 -0.07814 200 7.00E-05

A2 Proposed Mechanisms

210

iii) C4H

6O

4

O O

OH

OH

OHOH

O2O O

OH

OH

OHO

O

RO2O O

OH

OH

OHO

Scheme 2

Scheme 3

Scheme 1

Scheme 2

O O

OH

OH

OHO

O

CH

O

OH

OH

OHO

O2

O O

OH

OH

OHOO

O

RO2

RO2

O O

OH

OH

OH

O OH

O O

OH

OH

OHOO

O O

OH

OH

OHOO

O O

OH

OH

OHOO

O O

OH

OH

OHOO

O O

OH

OH

OHOO

O

OH

OH

OH

O

O

O

+

O

O

O

OH

OH

OH

O

+O2

OH

OH

OHO

O

O

-HO2

O

OH

OHO

O O

OH

OH

OHOO

O

CH

O

OH

OH

OHOO

O2O O

OH

OH

OHOOO

O

O

O

OH

OH

O

O

O

Scheme 3

O O

OH

OH

OHO

O O

OH

OH

OHO

O O

OH

OH

OHO

O O

OH

OH

OHO

O

CH

O

OH

OH

OHO

O O

OH

OH

OHO

O

O

-HO2

O OO

OH

OH

O

C6H

8O

6

O O

OH

OH

OHO

O O

OH

OH

OHO

CH

O+

O O

OH

OH

OHO

O

CH

OH

OH

OH

OO

+

O2

O2O

OH

OH

OHO

O

-HO2

C6H

8O

7

-HO2

vii) C6H

10O

7

vi) C5H

8O

5

vi) C5H

8O

5

iii) C4H

6O

4

O O

OH

OH

OHO

O O

OH

OH

OHO-H2O

O

OH

OH

OH

O

Scheme 4

O

OH

OHO

O

O

OHO

OH

-H2O

C

O

OH

OHO

H2O

OH

O

OHO

OH

OH

-H2O

H2O

C

OH

O

OHO

OH

O2

OH

O

OHO

OHO

O

-HO2

O

O

OHO

OH

O

OH

OHO

OH

O2

-H2OO

OH

OHO

O O

-HO2

iv) C4H

4O

5

O2

O

OH

OHO

O

O

RO2

O

OH

OHO

O

-CO2

CH OH

OHOO2

OH

OHO

OO

O

OHO

OH

O2

-H2OO

OHO

OO-HO2

O

OO

ii) C3H

4O

3

i) C3H

2O

3

Scheme 5

Scheme 4

O

OH

OH

OH

O

Scheme 5

OH

O2

-H2O O

OH OH

OH

O

OO

-HO2

O

OH

O

OH

O

Scheme 4

Glyoxal

v) C5H

6O

5

vi) C5H

8O

5

iii) C4H

6O

4

-HO2

211

Figure A1: Proposed reaction mechanism giving rise to the products displayed in Figure 3.6 (main article). The overall

reaction mechanism of levoglucosan photooxidation is highly complicated, and only a subset is shown here. As one

example, the mechanism demonstrates the case when H-abstraction occurs at the position shown in Scheme 1.

Subsequent chain scission can lead to two different reaction pathways shown in Scheme 2 and Scheme 3, respectively.

Scheme 4 demonstrates that products from Scheme 3 can undergo the hydroxyl-to-carbonyl conversion which is

discussed in the functionalization section in the main article. Scheme 5 illustrates hydration of an aldehyde and its

subsequent conversion to a carboxylic acid.

A3 Estimation of the Diffusion Limited Rate Constant of LG Oxidation by OH Radicals in the Aqueous Phase.

We calculated the diffusion limited rate constant to be 1.9 × 109 M-1s-1, based on the following

Eqn. A1 (Pilling and Seakings, 1995):

k (M-1s-1) = 1000 × 4π × (rLG+rOH

2) × (DLG + DOH) × NA, (A1)

where 1000 is a conversion factor for units, rx and Dx represents the radius and diffusion coefficient

of molecule X in water, respectively, and NA is the Avogadro constant. The value of rLG is

estimated to be 0.22 nm, assuming LG is approximately half the size of a sucrose (a sugar dimer)

(Pappenheimer 1953). The value of rOH is assumed to be 0.1 nm, a typical O-H bond length of a

water molecule. The diffusion coefficient of glucose in water (0.6 × 10-9 m-2s-1, from Stein 1990)

is used as DLG, given the similarity between LG and glucose. The value of DOH (1 × 10-9 m-2s-1) is

adopted from Hanson et al. (1992).

Bibliography

Hanson, D. R., Burkholder, J. B., Howard, C. J. and Ravishankara, A. R.: Measurement of Oh and

Ho2 Radical Uptake Coefficients on Water and Sulfuric-Acid Surfaces, J. Phys. Chem., 96, 4979-

4985, 1992.

212

Pappenheimer, J. R.: Passage of Molecules through Capillary Walls, Physiol. Rev., 33, 387-423,

1953.

Pilling, M. J. and Seakins, P. W.: Reaction kinetics, Oxford University Press, Oxford England ;

New York, 1995.

Stein, W. D.: Channels, carriers, and pumps: an introduction to membrane transport, Academic

Press, San Diego, 1990.Pilling, M. J. and Seakins, P. W.: Reaction kinetics, Oxford University

Press, Oxford England ; New York, 1995.

213

Appendix B

Supplementary Information For:

Chapter 4

Formation of Aqueous-phase α-hydroxyhydroperoxides (α-HHP):

Potential Atmospheric Impacts

As published in Atmos. Chem. Phys. 13, 5857–5872. DOI:10.5194/acp-13-5857-2013

Distributed under the Creative Commons Attribution 3.0 License.

214

B1 Example 1H NMR Spectra and Peak Assignment for Each Carbonyl Compound.

The carbonyl-H2O2 mixtures at equilibrium are shown.

Figure B1: Glycolaldehyde (10 mM) and H2O2 (17.7 mM)

5x106

4

3

2

1

0

Sig

nal In

ten

sity (

AU

)

10 9 8 7 6 5 4 3 2 1 0

Chemical Shift (ppm)

(1, s)(5, t)

(3, t)

(2, s)

(6, d)

(4, d)

(DMSO, s)

Water

215

Figure B2: Methylglyoxal (10 mM) and H2O2 (17.7 mM).

10x106

8

6

4

2

0

Sig

nal In

tensity (

AU

)

8 7 6 5 4 3 2 1 0 -1

Chemical Shift (ppm)

5x106

4

3

2

1

0

Sig

nal In

tensity (

AU

)

4.90 4.80 4.70

Chemical Shift (ppm)

10x106

8

6

4

2

0

Sig

nal In

tensity (

AU

)

2.1 2.0 1.9 1.8

Chemical Shift (ppm)

4x106

3

2

1

0

Sig

nal In

tensity (

AU

)

1.2 1.0 0.8

Chemical Shift (ppm)

(formic acid, s)

(5, s)

(3, s)

(17, s)

(11, s)

(15, s)

water

(?, s)

(DMSO, s)

(6, s)

(4, s)

(?, s) (16, d)

(10, d)

(18, d)

216

E

Figure B3: Propionaldehyde (10 mM) and H2O2 (17.7 mM).

4x106

3

2

1

0

Sig

nal In

ten

sity (

AU

)

10 9 8 7 6 5 4 3 2 1 0 -1 -2 -3

Chemical Shift (ppm)

1.0x106

0.8

0.6

0.4

0.2

0.0

Sig

nal In

tensity (

AU

)

4.85 4.80 4.75

Chemical Shift (ppm)

3.5x106

3.0

2.5

2.0

1.5

1.0

0.5

0.0

Sig

nal In

tensity (

AU

)

0.80 0.70 0.60

Chemical Shift (ppm)

(1, t)

(7, t)

(4, t)

(DMSO, s)

(2, dq)

(5 and 8, multi)

(3, t)

(9, t)

(6, t)

water

217

Figure B4: Glyoxal (10 mM) and H2O2 (17.7 mM).

10x106

8

6

4

2

0

Sig

nal In

ten

sity (

AU

)

10 9 8 7 6 5 4 3 2 1 0

Chemical Shift (ppm)

(DMSO, s)(formic acid, s)

water

(?, q)

(2?, d)

(?, s)

218

Figure B5: Glyoxylic acid (10 mM) and H2O2 (17.7 mM).

5x106

4

3

2

1

0

Sig

nal In

ten

sity (

AU

)

10 9 8 7 6 5 4 3 2 1 0

Chemical Shift (ppm)

(formic acid, s)

(2, s)

(DMSO, s)

(?, s)

219

Figure B6: Methacrolein (10 mM) and H2O2 (100 mM).

5x106

4

3

2

1

0

Sig

nal In

ten

sity (

AU

)

10 9 8 7 6 5 4 3 2 1 0

Chemical Shift (ppm)

(1,s)

(DMSO,s)

water

(2, t)

(2, t)

(?, s)

(3, t)

220

Figure B7: Methylethyl ketone(10 mM) and H2O2 (100 mM).

20x106

15

10

5

0

Sig

nal In

ten

sity (

AU

)

10 9 8 7 6 5 4 3 2 1 0

Chemical Shift (ppm)

(DMSO, s)

water

(2, q)

(1, s)

(3, t)

(?, d)

221

Figure B8: Acetone (10 mM) and H2O2 (100 mM).

150x106

100

50

0

Sig

nal In

ten

sity (

AU

)

10 9 8 7 6 5 4 3 2 1 0

Chemical Shift (ppm)

(DMSO, s)

(1, s)

(?, d)

water

222

Table B1. Comparison of Kapp values experimentally determined and calculated as (Keq/Kapp).

Keq determined

(M-1)

Khyd

determined

Keq / Khyd

(M-1)

Kapp determined

(M-1)

formaldehyde 1.66 × 106 2300* 723 164

acetaldehyde 230 1.43 161 113.5**

propionaldehyde 116 1.256 92 67.5**

glycolaldehyde 727 16 45 43.3

*Was not determined from the current work, but taken from Betterton and Hoffmann 1988.

** Are the averaged values from the 1H NMR and the PTR-MS measurements.

Bibliography

Betterton, E. A. and Hoffmann, M. R.: Henry law constants of some environmentally important

aldehydes, Environ. Sci. Technol., 22, 1415-1418, 1988.

223

Appendix C

Supplementary Information For:

Chapter 5

Photochemical Processing of Aqueous Atmospheric Brown Carbon

As published in Atmos. Chem. Phys. Discuss. 15: 2957-2996, DOI:10.5194/acpd-15-2957-2015.

Distributed under the Creative Commons Attribution 3.0 License.

224

C1 Determination of Photon Flux in the Solar Simulator

The output of the solar simulator was recorded using the detector of the liquid waveguide capillary

UV-Vis spectrometer described in the main article Section 2.2. This method qualitatively

determines the spectral shape of the simulated sunlight.

Meanwhile, chemical actinometry using 2-nitrobenzaldehyde (2NB) was employed to

quantitatively evaluate the simulated sunlight. This chemical actinometer has been employed

previously by Anastasio and coworkers for quantification of photon flux in aqueous phase and ice.

The absorption cross section, as well as the recommended quantum yield of this compound, are

provided by Galbavy et al. (2012).

A 2NB solution (200 uM, 100 mL) was prepared and was illuminated in the solar simulator.

Aliquots were taken every two minutes for offline analyses. Measurement of 2NB was conducted

using a high performance liquid chromatography (HPLC) system equipped with a Perkin Elmer

Series 200 pump, a Shimadzu SPD-10A UV-Vis detector, a Waters Symmetry® C18 column (5

µm pore size, 4.6 mm diameter and 150 mm column length). A mixture of acetonitrile and water

(60 : 40) was used as the mobile phase in isocratic mode, with a flow rate of 1 mL / min. Absorption

at 256 nm was monitored for the detection of 2NB.

Using the absorption cross section and recommended quantum yield of 2NB (Galbavy et al. 2010),

we scaled the recorded output spectra from the solar simulator to match the observed decay rate of

2NB. The photon flux determined this way is shown in Figure C1, along with ambient actinic flux

at the Earth’s surface with a zenith angle of 0 ˚ (Finlayson-Pitts and Pitts 2000).

The integrated photon flux between 290 and 380 nm is similar between the simulated and ambient

photon flux. Although the simulator supplies more photo photons than the ambient at longer

wavelengths, we assume that they are fairly similar, as we do not know what wavelengths are

responsible for BrC photolysis (i.e. the quantum yields are unknown).

225

Figure C1: The photon flux in the solar simulator and in the ambient.

C2 Quantitative Assessment of BrC Absorption

C2.1 Imine BrC

The mass absorption coefficients (MAC) of the GLYAS and MGAS solutions were calculated.

While it is difficult to estimate the amount of BrC in the solution, we used the total organic carbon

(TOC) content of the solution to calculate MAC. The concentrated stock solutions of GLYAS and

MGAS were diluted by a factor of 100, and the TOC content of the diluted solutions was measured

using a Shimadzu TOC-ICPH Total Organic Analyzer. The wavelength dependent MAC(λ) is

calculated based on Eqn. C1 (Lee et al. 2014):

MAC(λ) = A(λ) × ln (10)

b × Cmass, (C1)

where A(λ) is the base-10 absorbance observed at wavelength λ, b is the effective path length of

the liquid capillary waveguide (50 cm), and Cmass is the mass concentration (g cm-3) of total organic

carbon in the solution. The MAC(λ) values of GLYAS and MGAS calculated using Eqn. C1 are

shown in Figure C2(a).

226

C2.2 WSOC from Biofuel Combustion Samples

Calculations of the MAC for the biofuel combustion samples are conducted based on the organic

matter (OM) contents measured by an OM/OC method described by Chan et al. (2010). MAC(λ)

was calculated similar to Imine BrC using Eqn. C1 and is shown in Figure C2(b). We consider the

MAC determined in the current method a lower limit for these sample because: 1) particles freshly

emitted from BB likely contain a large fraction of non-light absorbing organic compounds (Chen

and Bond 2010), and 2) WSOC presents only a fraction of the total OM content of the particle,

and the extraction efficiency is unknown.

The Angstrom absorption coefficients (AAE) between 290 nm and 480 nm were calculated using

Eqn. C2 (Chen and Bond 2010) and are reported in the main article:

AAE = ln (

MAC(λ1)MAC(λ2)⁄ )

ln (λ1λ2⁄ )

. (C2)

C2.3 Nitrophenols

Since the nitrophenols are pure compounds, their wavelength dependent molar absorptivity (ε(λ))

and absorption cross section (σ(λ)) are calculated based on Eqn. C3 and C4, respectively.

ε(λ) = A(λ)

c ×b (C3)

σ(λ) = 1.66 × 10-21ε (C4)

Eqn. C3 is based on the Beer-Lambert law, where A(λ) is the base-10 absorbance observed at

wavelength λ, c is the molarity of the nitrophenol (M), and b is the effective path length of the

liquid capillary waveguide (50 cm). Eqn. C4 converts ε(λ) to σ(λ) (both in base 10) (Finlayson-

Pitts and Pitts, 2000). The calculated ε(λ)and σ(λ) are displayed in Figure C2(c).

227

a) b)

c)

Figure C2: Wavelength dependent mass absorption coefficient (MAC) for the Imine BrC (a), the WSOC from biofuel

combustion samples (b), and the base 10 absorption cross section and molar absorptivity of the nitrophenols (c).

228

C3 Concentration Dependence of Imine BrC Decay Rate

Figure C3: Decay of the GLYAS solution (a) and the MGAS solution (b) during the first 10 min of illumination at

different initial concentrations.

C4 Spectral Change of 4NP and 5NG during Direct Photolysis

Figure C4: Spectral change observed for a 4NP solution (a) and a 5NG solution (b) during direct photolysis

experiments. The initial concentrations of 4NP and 5NG were 5 µM and 4 µM, respectively. The insets illustrate the

absorbance change compared to the initial conditions.

229

C5 pH Dependent Photo-enhancement of 4NP and 5NG and OH Scavenger Experiments

We investigated the photo-enhancement of the nitrophenols at solution pH of 3, 4 and 5. We also

conducted an OH scavenger experiment where glyoxal (1 mM) was added to a pH 5 solution to

react OH radicals away.

The OH scavenger experiment affects the photo-enhancement rate of 4NP, but did not completely

shut down the reaction. 5NG was not affected by the OH scavenger. The photo-enhancement rate

of 4NP at 420 nm exhibited irregularity (Figure C5(a)), perhaps due to the fact that 420 nm was

close to the isosbestic point of 4NP absorption. When we plotted the photo-enhancement of 4NP

at a longer wavelength, 450 nm (Figure C5(b)), we observed a clearer pH dependence. 5NG

exhibited a unique pH dependence (Figure C5(c)), where the photo-enhancement was suppressed

significantly when the pH was 3.

For 4NP and 5NG, the formation of color exhibited strong linearity in time, which prevented us

from fitting a 1st order growth curve to extract kIdirect. Therefore, we decided to present the rate of

photo-enhancement (k*direct) in an absorbance based manner using Eqn. C5 in units of [AU M-1 s-

1]:

k*direct = S

60 × Cini⁄ (C5)

where S (AU min-1) is the initial slope of color formation found from Figure C5, 60 is the

conversion factor from minutes to seconds, and Cini (M) is the initial concentration of the

nitrophenol. The k*direct values obtained are summarized in Table C1. If the identity and molar

absorptivity of the reaction products are determined from future studies, these absorbance based

rate constants can be converted into concentration based constants.

230

Table C1: The absorbance based 1st order rate constant of photo-enhancement

Compound

Cini

(µM)

k*direct (AU M-1 s-1)

pH3 pH4 pH 5

pH 5 OH

scav.

4NP (420 nm) 15 0.68 0.62 0.40 0.24

4NP (450nm) 15 0.37 0.47 0.64 0.47

5NG (420 nm) 8 2.7 4.0 4.8 4.8

Figure C5: Color formation from 4NP and 5NG solutions during the pH dependent and the OH scavenger

experiments. The formation profiles of absorbance at 420 nm and 450 nm from 4NP are shown in (a) and (b). The

formation profiles of absorbance at 420 nm from 5NG are shown in (c).

231

C6 pH Dependent Absorption of Nitrophenols

Figure C6: Absorption spectra of 4NP (a), 5NG (b) and 4NC (c) at various solution pH values.

C7 Photooxidation of 4NP and 5NG

232

Figure C7: The spectral change of 4NP and 5NG solutions during OH oxidation experiments are shown in (a) and

(c). The time profiles of absorbance at 420 nm for 4NP and 5NG are shown in (b) and (d). In (b) and (d), the black

traces represent H2O2 control experiments, while the red traces represent OH oxidation experiments. The concentration

of 4NP and 5NG solutions are 15 µM and 8 µM, respectively.

C8 Simple Kinetic Model Applied to 4NP and 5NG

In this model, the precursor nitrophenols undergo prescribed pseudo-1st order decay with a [OH]ss

of 3.2 × 10-14 M. For the case of 4NP we also observed direct loss by photolysis (Figure C7(b)) by

the 254 nm lamp with a rate constant of 2.6 × 10-4 s-1. This direct photolysis was also added to the

prescribed decay of 4NP. The 2nd order rate constant of 4NP was adopted from Einschlag et al.

(2003): 6.2 × 109 M-1 s-1. Although the OH reactivity of 5NG and 4NC in the aqueous phase is not

available in the literature, we used 1 × 1010 M-1 s-1 as a rough estimate for these two compounds.

This estimation is based on the fact that the additional methoxy and hydroxy functional groups on

5NG and 4NC are electron donating and can likely enhance the OH reactivity. The model results

for sample 4NP and 5NG OH oxidation experiments are shown in Figure C8.

233

Figure C8: The simple kinetic model applied to one example experiment each of 4NP (a) and 5NG (b) OH oxidation.

The shaded areas are the simulated contribution of a newly formed colored product and the decay precursor. The red

lines represent the experimental results.

Bibliography

Chan, T. W., Huang, L., Leaitch, W. R., Sharma, S., Brook, J. R., Slowik, J. G., Abbatt, J. P. D.,

Brickell, P. C., Liggio, J. and Li, S.: Observations of OM/OC and specific attenuation coefficients

(SAC) in ambient fine PM at a rural site in central Ontario, Canada, Atmos. Chem. Phys., 10,

2393-2411, 2010.

Chen, Y. and Bond, T.: Light absorption by organic carbon from wood combustion, Atmos. Chem.

Phys., 10, 1773-1787, 2010.

Einschlag, F. S. G., Carlos, L. and Capparelli, A. L.: Competition kinetics using the UV/H2O2

process: a structure reactivity correlation for the rate constants of hydroxyl radicals toward

nitroaromatic compounds., Chemosphere, 53, 1-7, 2003.

Finlayson-Pitts, B. J. and Pitts, J. N.: Chemistry of the upper and lower atmosphere : theory,

experiments and applications, Academic Press, San Diego, Calif. ; London, 2000.

234

Galbavy, E. S., Ram, K. and Anastasio, C.: 2-Nitrobenzaldehyde as a chemical actinometer for

solution and ice photochemistry, J. Photochem. Photobiol. A., 209, 186-192, 2010.

Lee, H. J., Aiona, P. K., Laskin, A., Laskin, J. and Nizkorodov, S. A.: Effect of solar radiation on

the optical properties and molecular composition of laboratory proxies of atmospheric brown

carbon, Environ. Sci. Technol., 48, 10217-10226, 2014.

235

Appendix D

Supplementary Information For:

Chapter 6

Cloud Partitioning of Isocyanic Acid (HNCO) and Evidence of

Secondary Source of HNCO in Ambient Air

Reproduced with permission from Geophysical Research Letter (41), pp 6962–6969

DOI: 10.1002/2014GL061112 Copyright © 2014 American Geophysical Union.

236

D1 Map of the measurement sites

Figure D1: The current work was part of a collaborative field measurement at La Jolla, CA. Measurements were

performed concurrently at two locations: Mt. Soledad (A), and Scripps Pier (B). The current paper focuses on the

CIMS data obtained at site A.

D2 Calibration of the Acid-CIMS

D2.1 Calibration Methods

The HNCO calibration was performed using the same method as used previously [Wentzell et al.,

2013]. Nitrogen was introduced through a HNCO source containing cyanuric acid (trimer of

HNCO) and heated to 200 ˚C. The output of the source was then quantified using ion

chromatography as NCO-.

Commercial permeation tubes were used for the calibration of nitric acid (HNO3).

D2.2 Calibration factors and limits of quantification of HNCO and HNO3

Table D1: Calibration factors of the Acid CIMS.

237

Name

Chemical

formula

Limit of quantification

(LOQ) (pptv)a

Calibration Factor

(ncps/ppbv)b

isocyanic acid HNCO 11 0.446

HNO3 HNO3 6.2 0.69

a LOQ was determined as 10 times the standard deviation of the background signal of each compound over a 30 min

time integral.

b The calibration factor is presented as normalized counts per second (ncps) per parts per billion by volume (ppbv) of

the targeted compound. Signals of the analytes were normalized against the reagent ion at m/z = 61 (one of the isotopes

of acetate). The signal at m/z 61 is typically 2.5 × 104 cps.

D3 Quantification of HNCO and HNO3 in CVI.

D3.1 CVI Background

While the CIMS background during the ambient measurement is the time period during which the

inlet flow is directed through a bicarbonate denuder, the background during the CVI periods is

different. Since compressed air used as the counterflow contains impurities, the background during

CVI measurements is the period when there is no cloud droplet sampled (i.e. analyte signals come

solely from the compressed air). We used the signals during periods where liquid water content

(LWC) was below its 10th percentile as the background period of the CVI. When LWC is low,

HNCO and HNO3 from droplet evaporation are negligible, and the detected signals should reflect

their levels in the compressed air used.

D3.2 Normalization and Quantification

The raw signal was normalized against the reagent ion at m/z 61, before the CVI background was

corrected (Sect. S3.1.). After that, the same calibration factors (see Sect. S2.) were used to convert

signals to mixing ratios.

238

D4 Calculating the Aqueous Fraction of HNCO (faq,HNCO)

As defined in the main article, faq,HNCO is the fraction of total HNCO present in a LWC of 0.1 g m-

3. faq,HNCO is the ratio between the aqueous-phase concentration of HNCO and the total amount of

HNCO, taking into account CVI parameters (Eqn. D1). This section provides explanations for

each of the parameter used in S1. For more details about specific CVI parameters, please refer to

Schroder et al. (2014).

faq,HNCO =S×0.1

[HNCO]CIMS,pre-cloud ×

1

EF ×

1

DT × fliquid (D1)

S – The slope obtained from linear fitting of [HNCO]CVI vs. LWC (Figure 6.1c in the main article).

EF – Enhancement factor of the CVI. See Sect. S4.1. for details.

DT– Droplet transmission in the CVI. See Sect S4.2. for details.

fliquid – Fraction of LWC in the ambient air sampled by the CVI. See Sect. S4.3. for details.

The values for the parameters above are summarized in Table D2, and the time series of the

calculated faq,HNCO is shown in Figure D2.

Table D2: The parameters from the June 1st and the June 13th cloud events are summarized. D50 represents the

calculated 50 % size cutoff of the CVI (the cloud droplet cut size).

Cloud

Event

S D50 EF f DT

June 1st 166 11.57 7.25 0.9705 0.2766

June 13th 171 11.48 7.14 0.9062 0.2601

239

Figure D2: Calculated time series of the aqueous-fraction of HNCO (faq,HNCO) during the June 1st and June 13th cloud

events.

D4.1 Determination of the Enhancement Factor (EF)

Cloud droplets sampled by the CVI is concentrated by an Enhancement Factor (EF) because wind

tunnel air speed (i.e. from the ambient to the CVI) is faster than the sample flow air speed (i.e.

from CVI to the instruments), resulting in a compression of air near the stagnant plane [Noone et

al. 1988]. In other words, the cloud droplets sampled by the CVI are enhanced in number by a

factor of the EF. EF is calculated in accordance with Noone et al. [1988] using Eqn. D2:

EF = Sw × π × r2

Ss (D2)

Sw – The wind tunnel air speed.

Ss – The sample flow air speed.

r – The inner radius of the CVI tip.

240

D4.2 Determination of Droplet Transmission (DT) in the CVI

The droplet transmission (DT) of the CVI used is not 100% due to slower drying of larger droplets

and an imperfectly aligned air stream with respect to the CVI axis, giving rise to droplet loss in

the CVI. The DT value is estimated by comparing the number concentration of cloud droplets in

the ambient air (Ndroplet) and evaporation residues in the CVI (NRes), monitored by the Fog Monitor

and the CPC, respectively. For Ndroplet, only droplets with diameters above the CVI cutoff are

considered (Ndroplet > D50). The NRes is divided by the EF to take the enhancement into

consideration. If there is no particle loss in the CVI, the slope of the plot should be 1 (the dashed

line). However, as shown in Figure D2., Ndroplet >D50 is significantly larger than NRes / EF,

reflecting droplet loss in the CVI. The DT values are obtained as the reciprocal of the slopes.

Figure D3: Comparison of number concentrations of cloud droplets in the ambient air (Ndroplet >D50), and evaporation

residue in the CVI (NRes) divided by the calculated EF. Data from the June 1st event (a) and the June 13th event (b) are

shown. The dashed line represents a line with a slope of one, whereas the solid line shows the actual linear fitting.

Droplet Transmission (DT) is obtained as the reciprocal of the slope.

241

D4.3 Determination of the fraction of LWC sampled by CVI (fliquid)

The fraction of LWC sampled by the CVI (term fliquid in Eqn. D1) is estimated from the size

distributions of the cloud droplets in the ambient air (Figure D4). As shown in Figure D4, the CVI

did not sample a significant fraction of the small droplets in terms of number, but may have

sampled the majority of the liquid volume and surface area. The fraction of volume concentration

above the cut-off are presented by the fliquid term.

Figure D4: The size distribution of number (black), volume (blue) and surface area (green) concentration of cloud

droplets in the ambient air during the June 1st (a) and the June 13th (b) events, monitored by the Fog Monitor. The

dashed lines represent calculated 50 % size cut-off of the CVI.

D4.4 Error propagation for faq,HNCO

The relative uncertainty of the obtained faq,HNCO is estimated to be 19 %, by propagating the error

of each parameters used in Eqn. D1. The error of each of the parameters is explained here:

S – the relative error is estimated to be 10 % based on the scatter of [HNCO]CVI vs LWC (Figure

6.1c) in the main article.

242

EF – the relative error is estimated to be 15 %. The error of EF arises from the uncertainty of the

wind speed (Sw and Ss in Eqn. D2). Their relative errors are approximately 10% each.

DT – the relative error is estimated to be 5 %, based on the scatter of Figure D3.

fliquid – the relative error is estimated to be 5 %, based on the relative error of the CVI cut size.

D4.5 A sensitivity test for faq,HNCO

Since each of the parameter mentioned above directly affects the accuracy of the calculated

faq,HNCO, we performed a simple sensitivity test by calculating faq,HNCO under a “perturbed case”

(Table D3). The perturbed case represents an extreme, unlikely case, where [HNCO]pre-cloud and

EF are twice as large as the actual value, and there is no particle loss in the CVI (i.e. fliquid = 1).

We consider the perturbed case the maximum extent to which systematic errors can affect our

calculated faq,HNCO.

Table D3: A comparison of the calculated faq,HNCO in the actual case and a perturbed case. The perturbed values are

highlighted in red.

Event S

[HNCO]pre-

cloud (pptv) EF fliquid DT

LWC (g

m-3) faq,HNCO

June1st Actual case 0.17 48 7.25 0.97 0.28 0.1 0.17

Perturbed case 0.17 96 14.5 0.97 1 0.1 0.012

June13th Actual case 0.17 115 7.14 0.91 0.26 0.1 0.073

Perturbed case 0.17 230 14.28 0.91 1 0.1 0.0047

243

D5 The pH-dependence of KHeff of HNCO and the theoretical aqueous fraction of HNCO (faq,HNCO)

Figure D5: Calculated KHeff of HNCO as a function of pH, based on data reported by [Roberts et al., 2011] is shown

in (a). The measured pH of bulk cloud water samples collected during the June 1st Event (Blue) and the June 13th

Event (red) are also shown as the dashed lines. The KHeff at these two pH values are 3.0 × 103 and 8.0 × 102 M atm-1,

respectively. Based on the KHeff values shown on (a), the theoretical aqueous fraction of HNCO (faq,HNCO) is calculated

as a function of pH and LWC (b).The calculations assume complete Henry’s law equilibrium between the gas and

aqueous phases.

244

D6 Time series and diurnal profiles of HNCO, formic acid and ambient temperature

Figure D6: Time series of HNCO, formic acid and ambient temperature during a specific period

of the campaign are shown in (a). Clear correlations between these traces can be seen. The

campaign-averaged diurnal profiles are shown in (b). The peak of HNCO mixing ratio is reached

at similar time as the other traces shown here.

245

D7 Strength of correlation between HNCO and BC during various time periods

Figure D7: Linear fitting between HNCO and Black Carbon (BC) was performed for various time periods of each

measurement day, and R2 values from the fitting are shown here. The correlation is typically strongest during morning

rush hours (5am to 8am; black). The differences are statistically significant at the 95% confidence level. This is an

indication that there might be a primary source of HNCO during the morning rush hour.

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